医疗人工智能

10000 条实体 · 最后更新 2026-09-01T06:00:42.666Z · Workforce / Literacy / Applications of artificial intelligence / Engineering ethics / Workforce development / Nontuberculous mycobacteria / Scope (computer science) / Genomics / Artificial intelligence / Computational biology / Dementia / Differential diagnosis

• Machine Learning Systems in the IoT: Trustworthiness Trade-offs for Edge Intelligence
  Machine learning systems (MLSys) are emerging in the Internet of Things (IoT) to provision edge intelligence, which is paving our way towards the vision of ubiquitous intelligence. However, despite the maturity of machine learning systems and the IoT, we are f…
  arxiv Wiebke Toussaint, Aaron Yi Ding 2020-12-01T11:42:34Z 置信度 0.78 cs.LGcs.CY
• Fish Tracking Challenge 2024: A Multi-Object Tracking Competition with Sweetfish Schooling Data
  The study of collective animal behavior, especially in aquatic environments, presents unique challenges and opportunities for understanding movement and interaction patterns in the field of ethology, ecology, and bio-navigation. The Fish Tracking Challenge 202…
  arxiv Makoto M. Itoh, Qingrui Hu, Takayuki Niizato, Hiroaki Kawashima 等 2024-08-31T03:26:53Z 置信度 0.78 cs.CV
• The impact of artificial intelligence: from cognitive costs to global inequality
  In this paper, we examine the wide-ranging impact of artificial intelligence on society, focusing on its potential to both help and harm global equity, cognitive abilities, and economic stability. We argue that while artificial intelligence offers significant …
  arxiv Guy Paić, Leonid Serkin 2025-03-11T05:49:00Z 置信度 0.78 physics.soc-phcs.CY
• ScribFormer: Transformer Makes CNN Work Better for Scribble-based Medical Image Segmentation
  Most recent scribble-supervised segmentation methods commonly adopt a CNN framework with an encoder-decoder architecture. Despite its multiple benefits, this framework generally can only capture small-range feature dependency for the convolutional layer with t…
  arxiv Zihan Li, Yuan Zheng, Dandan Shan, Shuzhou Yang 等 2024-02-03T04:55:22Z 置信度 0.78 cs.CVcs.AIcs.LG
• Artificial Intelligence in Cybersecurity: Building Resilient Cyber Diplomacy Frameworks
  This paper explores how automation and artificial intelligence (AI) are transforming U.S. cyber diplomacy. Leveraging these technologies helps the U.S. manage the complexity and urgency of cyber diplomacy, improving decision-making, efficiency, and security. A…
  arxiv Michael Stoltz 2024-11-17T17:57:17Z 置信度 0.78 cs.CRcs.AIcs.CY
• MC-CPO: Mastery-Conditioned Constrained Policy Optimization for Pedagogically Safe Intelligent Tutoring Systems
  Intelligent tutoring systems increasingly rely on reinforcement learning to personalise instruction, yet optimising for observable engagement signals can systematically decouple learner activity from genuine knowledge acquisition. Analysing over 21 million stu…
  arxiv Oluseyi Olukola, Nick Rahimi 2026-04-05T20:13:34Z 置信度 0.78 cs.AIcs.CYcs.LG
• Robustness of an Artificial Intelligence Solution for Diagnosis of Normal Chest X-Rays
  Purpose: Artificial intelligence (AI) solutions for medical diagnosis require thorough evaluation to demonstrate that performance is maintained for all patient sub-groups and to ensure that proposed improvements in care will be delivered equitably. This study …
  arxiv Tom Dyer, Jordan Smith, Gaetan Dissez, Nicole Tay 等 2022-08-31T09:54:24Z 置信度 0.78 eess.IVcs.AI
• A Meta-Analysis of the Utility of Explainable Artificial Intelligence in Human-AI Decision-Making
  Research in artificial intelligence (AI)-assisted decision-making is experiencing tremendous growth with a constantly rising number of studies evaluating the effect of AI with and without techniques from the field of explainable AI (XAI) on human decision-maki…
  arxiv Max Schemmer, Patrick Hemmer, Maximilian Nitsche, Niklas Kühl 等 2022-05-10T19:08:10Z 置信度 0.78 cs.HCcs.AI
• Massive geolocation data reveal evacuation behaviour during the 2024 Noto Peninsula earthquake and tsunami
  On 1 January 2024, devastating tsunamis caused by the Noto Peninsula earthquake hit coastal areas within several minutes, but only two tsunami casualties were officially reported. Despite its importance, the cause of this unexpectedly low human loss was unclea…
  arxiv Fumiyasu Makinoshima, Saki Yotsui, Shosuke Sato, Fumihiko Imamura 2024-12-08T03:16:33Z 置信度 0.78 physics.soc-ph
• An artificial intelligence and Internet of things based automated irrigation system
  It is not hard to see that the need for clean water is growing by considering the decrease of the water sources day by day in the world. Potable fresh water is also used for irrigation, so it should be planned to decrease freshwater wastage. With the developme…
  arxiv Ömer Aydin, Cem Ali Kandemir, Umut Kiraç, Feriştah Dalkiliç 2021-04-01T21:05:26Z 置信度 0.78 cs.CYcs.AIcs.LG
• Perceptions of Discriminatory Decisions of Artificial Intelligence: Unpacking the Role of Individual Characteristics
  This study investigates how personal differences (digital self-efficacy, technical knowledge, belief in equality, political ideology) and demographic factors (age, education, and income) are associated with perceptions of artificial intelligence (AI) outcomes …
  arxiv Soojong Kim 2024-10-17T06:18:26Z 置信度 0.78 cs.HCcs.AIcs.CY
• A Systematic Approach to Artificial Agents
  Agents and agent systems are becoming more and more important in the development of a variety of fields such as ubiquitous computing, ambient intelligence, autonomous computing, intelligent systems and intelligent robotics. The need for improvement of our basi…
  arxiv Mark Burgin, Gordana Dodig-Crnkovic 2009-02-20T04:58:40Z 置信度 0.78 cs.AIcs.MA
• Sustainable Materials Discovery in the Era of Artificial Intelligence
  Artificial intelligence (AI) has transformed materials discovery, enabling rapid exploration of chemical space through generative models and surrogate screening. Yet current generative AI models for materials discovery, which now drive exploration of vast chem…
  arxiv Sajid Mannan, Rupert J. Myers, Rohit Batra, Rocio Mercado 等 2026-01-29T10:42:44Z 置信度 0.78 cond-mat.mtrl-scics.AI
• A Picture May Be Worth a Thousand Lives: An Interpretable Artificial Intelligence Strategy for Predictions of Suicide Risk from Social Media Images
  The promising research on Artificial Intelligence usages in suicide prevention has principal gaps, including black box methodologies, inadequate outcome measures, and scarce research on non-verbal inputs, such as social media images (despite their popularity t…
  arxiv Yael Badian, Yaakov Ophir, Refael Tikochinski, Nitay Calderon 等 2023-02-19T06:18:23Z 置信度 0.78 cs.AIcs.CVcs.CY
• Medical world models: representing medical states, modelling clinical dynamics and guiding intervention policies
  Medical diagnosis and treatment are dynamic processes in which patient states evolve over time and clinical interventions alter future outcomes. Although current medical AI can detect disease, estimate risk and generate reports, many systems still return stati…
  arxiv Ke Liu, Mengxuan Li, Yanyi Bao, Tianyun Zhang 等 2026-06-15T13:49:43Z 置信度 0.78 cs.AI
• The economic alignment problem of artificial intelligence
  Artificial intelligence (AI) is advancing exponentially and is likely to have profound impacts on human wellbeing, social equity, and environmental sustainability. Here we argue that the "alignment problem" in AI research is also an economic alignment problem,…
  arxiv Daniel W. O'Neill, Stefano Vrizzi, Noemi Luna Carmeno, Felix Creutzig 等 2026-02-25T12:22:46Z 置信度 0.78 econ.GNcs.CY
• HySTER: A Hybrid Spatio-Temporal Event Reasoner
  The task of Video Question Answering (VideoQA) consists in answering natural language questions about a video and serves as a proxy to evaluate the performance of a model in scene sequence understanding. Most methods designed for VideoQA up-to-date are end-to-…
  arxiv Theophile Sautory, Nuri Cingillioglu, Alessandra Russo 2021-01-17T11:07:17Z 置信度 0.78 cs.CVcs.AIcs.CLcs.LO
• Clinical Decision Support System for Unani Medicine Practitioners
  Like other fields of Traditional Medicines, Unani Medicines have been found as an effective medical practice for ages. It is still widely used in the subcontinent, particularly in Pakistan and India. However, Unani Medicines Practitioners are lacking modern IT…
  arxiv Haider Sultan, Hafiza Farwa Mahmood, Noor Fatima, Marriyam Nadeem 等 2023-10-24T13:49:18Z 置信度 0.78 cs.AI
• Cracking the Code: Enhancing Development finance understanding with artificial intelligence
  Analyzing development projects is crucial for understanding donors aid strategies, recipients priorities, and to assess development finance capacity to adress development issues by on-the-ground actions. In this area, the Organisation for Economic Co-operation…
  arxiv Pierre Beaucoral 2025-02-13T17:01:45Z 置信度 0.78 econ.GNcs.AIcs.LG
• Agent Hospital: A Simulacrum of Hospital with Evolvable Medical Agents
  The recent rapid development of large language models (LLMs) has sparked a new wave of technological revolution in medical artificial intelligence (AI). While LLMs are designed to understand and generate text like a human, autonomous agents that utilize LLMs a…
  arxiv Junkai Li, Yunghwei Lai, Weitao Li, Jingyi Ren 等 2024-05-05T14:53:51Z 置信度 0.78 cs.AI
• Defining and Explorting the Intelligence Space
  Intelligence is a difficult concept to define, despite many attempts at doing so. Rather than trying to settle on a single definition, this article introduces a broad perspective on what intelligence is, by laying out a cascade of definitions that induces both…
  arxiv Paul S. Rosenbloom 2023-06-10T18:05:16Z 置信度 0.78 cs.AIcs.LG
• The Interspeech 2024 Challenge on Speech Processing Using Discrete Units
  Representing speech and audio signals in discrete units has become a compelling alternative to traditional high-dimensional feature vectors. Numerous studies have highlighted the efficacy of discrete units in various applications such as speech compression and…
  arxiv Xuankai Chang, Jiatong Shi, Jinchuan Tian, Yuning Wu 等 2024-06-11T21:08:47Z 置信度 0.78 cs.SDeess.AS
• MCGM: Mask Conditional Text-to-Image Generative Model
  Recent advancements in generative models have revolutionized the field of artificial intelligence, enabling the creation of highly-realistic and detailed images. In this study, we propose a novel Mask Conditional Text-to-Image Generative Model (MCGM) that leve…
  arxiv Rami Skaik, Leonardo Rossi, Tomaso Fontanini, Andrea Prati 2024-10-01T08:13:47Z 置信度 0.78 cs.CVcs.AI
• FlyAI -- The Next Level of Artificial Intelligence is Unpredictable! Injecting Responses of a Living Fly into Decision Making
  In this paper, we introduce a new type of bionic AI that enhances decision-making unpredictability by incorporating responses from a living fly. Traditional AI systems, while reliable and predictable, lack nuanced and sometimes unseasoned decision-making seen …
  arxiv Denys J. C. Matthies, Ruben Schlonsak, Hanzhi Zhuang, Rui Song 2024-09-30T17:19:59Z 置信度 0.78 cs.NE
• Sympathetic solar eruption on 2024 February 9
  In this paper, we perform a follow-up investigation of the solar eruption originating from active region (AR) 13575 on 2024 February 9. The primary eruption of a hot channel (HC) generates an X3.4 class flare, a full-halo coronal mass ejection (CME), and an ex…
  arxiv Shu-Yue Li, Qing-Min Zhang, Bei-Li Ying, Li Feng 等 2024-12-02T05:00:56Z 置信度 0.78 astro-ph.SR
• How to Build the Virtual Cell with Artificial Intelligence: Priorities and Opportunities
  The cell is arguably the most fundamental unit of life and is central to understanding biology. Accurate modeling of cells is important for this understanding as well as for determining the root causes of disease. Recent advances in artificial intelligence (AI…
  arxiv Charlotte Bunne, Yusuf Roohani, Yanay Rosen, Ankit Gupta 等 2024-09-18T02:41:50Z 置信度 0.78 q-bio.QMcs.AIcs.LGq-bio.NC
• 3D CBCT Challenge 2024: Improved Cone Beam CT Reconstruction using SwinIR-Based Sinogram and Image Enhancement
  In this paper, we present our approach to the 3D CBCT Challenge 2024, a part of ICASSP SP Grand Challenges 2024. Improvement in Cone Beam Computed Tomography (CBCT) reconstruction has been achieved by integrating Swin Image Restoration (SwinIR) based sinogram …
  arxiv Sasidhar Alavala, Subrahmanyam Gorthi 2024-06-12T10:01:00Z 置信度 0.78 eess.IVcs.CV
• Optimization for Medical Image Segmentation: Theory and Practice when evaluating with Dice Score or Jaccard Index
  In many medical imaging and classical computer vision tasks, the Dice score and Jaccard index are used to evaluate the segmentation performance. Despite the existence and great empirical success of metric-sensitive losses, i.e. relaxations of these metrics suc…
  arxiv Tom Eelbode, Jeroen Bertels, Maxim Berman, Dirk Vandermeulen 等 2020-10-26T11:45:55Z 置信度 0.78 eess.IVcs.CVcs.LG
• The Database and Benchmark for the Source Speaker Tracing Challenge 2024
  Voice conversion (VC) systems can transform audio to mimic another speaker's voice, thereby attacking speaker verification (SV) systems. However, ongoing studies on source speaker verification (SSV) are hindered by limited data availability and methodological …
  arxiv Ze Li, Yuke Lin, Tian Yao, Hongbin Suo 等 2024-06-07T14:13:20Z 置信度 0.78 eess.AS
• Exploring Teachers' Perception of Artificial Intelligence: The Socio-emotional Deficiency as Opportunities and Challenges in Human-AI Complementarity in K-12 Education
  In schools, teachers play a multitude of roles, serving as educators, counselors, decision-makers, and members of the school community. With recent advances in artificial intelligence (AI), there is increasing discussion about how AI can assist, complement, an…
  arxiv Soon-young Oh, Yongsu Ahn 2024-05-20T15:43:04Z 置信度 0.78 cs.HCcs.AIcs.CY
• Intelligence Sequencing and the Path-Dependence of Intelligence Evolution: AGI-First vs. DCI-First as Irreversible Attractors
  The trajectory of intelligence evolution is often framed around the emergence of artificial general intelligence (AGI) and its alignment with human values. This paper challenges that framing by introducing the concept of intelligence sequencing: the idea that …
  arxiv Andy E. Williams 2025-03-22T08:09:04Z 置信度 0.78 cs.AI
• MasonPerplexity at Multimodal Hate Speech Event Detection 2024: Hate Speech and Target Detection Using Transformer Ensembles
  The automatic identification of offensive language such as hate speech is important to keep discussions civil in online communities. Identifying hate speech in multimodal content is a particularly challenging task because offensiveness can be manifested in eit…
  arxiv Amrita Ganguly, Al Nahian Bin Emran, Sadiya Sayara Chowdhury Puspo, Md Nishat Raihan 等 2024-02-03T00:23:36Z 置信度 0.78 cs.CL
• A Manifesto for a Pro-Actively Responsible AI in Education
  This paper examines the historical foundations, current practices, and emerging challenges for Artificial Intelligence in Education (AIED) within broader AI practices. It highlights AIED's unique and rich potential for contributing to the current AI policy and…
  arxiv Kaska Porayska-Pomsta 2024-05-03T14:23:41Z 置信度 0.78 cs.CYcs.AI
• A Comprehensive Perspective on Explainable AI across the Machine Learning Workflow
  Artificial intelligence is reshaping science and industry, yet many users still regard its models as opaque "black boxes". Conventional explainable artificial-intelligence methods clarify individual predictions but overlook the upstream decisions and downstrea…
  arxiv George Paterakis, Andrea Castellani, George Papoutsoglou, Tobias Rodemann 等 2025-08-15T15:15:25Z 置信度 0.78 cs.LGcs.AI
• Bittensor Protocol: The Bitcoin in Decentralized Artificial Intelligence? A Critical and Empirical Analysis
  This paper investigates whether Bittensor can be considered the Bitcoin of decentralized Artificial Intelligence by directly comparing its tokenomics, decentralization properties, consensus mechanism, and incentive structure against those of Bitcoin. Leveragin…
  arxiv Elizabeth Lui, Jiahao Sun 2025-06-29T12:07:48Z 置信度 0.78 cs.CRcs.AI
• Rapid Automated Analysis of Skull Base Tumor Specimens Using Intraoperative Optical Imaging and Artificial Intelligence
  Background: Accurate diagnosis of skull base tumors is essential for providing personalized surgical treatment strategies. Intraoperative diagnosis can be challenging due to tumor diversity and lack of intraoperative pathology resources. Objective: To develop …
  arxiv Cheng Jiang, Abhishek Bhattacharya, Joseph Linzey, Rushikesh S. Joshi 等 2021-08-08T02:49:29Z 置信度 0.78 cs.CVcs.AIcs.LG
• Look: AI at Work! -- Analysing Key Aspects of AI-support at the Work Place
  In this paper we present an analysis of technological and psychological factors of applying artificial intelligence (AI) at the work place. We do so for a number of twelve application cases in the context of a project where AI is integrated at work places and …
  arxiv Stefan Schiffer, Anna Milena Rothermel, Alexander Ferrein, Astrid Rosenthal-von der Pütten 2025-09-02T12:51:23Z 置信度 0.78 cs.HCcs.AI
• Value Under Ignorance in Universal Artificial Intelligence
  We generalize the AIXI reinforcement learning agent to admit a wider class of utility functions. Assigning a utility to each possible interaction history forces us to confront the ambiguity that some hypotheses in the agent's belief distribution only predict a…
  arxiv Cole Wyeth, Marcus Hutter 2025-12-18T21:34:50Z 置信度 0.78 cs.AI
• Navigating Incommensurability Between Ethnomethodology, Conversation Analysis, and Artificial Intelligence
  Like many research communities, ethnomethodologists and conversation analysts have begun to get caught up -- yet again -- in the pervasive spectacle of surging interests in Artificial Intelligence (AI). Inspired by discussions amongst a growing network of rese…
  arxiv Stuart Reeves 2022-06-19T23:07:09Z 置信度 0.78 cs.HCcs.AI
• Semi-Supervised Siamese Network for Identifying Bad Data in Medical Imaging Datasets
  Noisy data present in medical imaging datasets can often aid the development of robust models that are equipped to handle real-world data. However, if the bad data contains insufficient anatomical information, it can have a severe negative effect on the model'…
  arxiv Niamh Belton, Aonghus Lawlor, Kathleen M. Curran 2021-08-16T14:52:20Z 置信度 0.78 cs.CVcs.LG
• Validity Arguments For Constructed Response Scoring Using Generative Artificial Intelligence Applications
  The rapid advancements in large language models and generative artificial intelligence (AI) capabilities are making their broad application in the high-stakes testing context more likely. Use of generative AI in the scoring of constructed responses is particul…
  arxiv Jodi M. Casabianca, Daniel F. McCaffrey, Matthew S. Johnson, Naim Alper 等 2025-01-04T16:59:29Z 置信度 0.78 cs.CLcs.AIcs.CY
• The Impact of Artificial Intelligence on Enterprise Decision-Making Process
  Artificial intelligence improves enterprise decision-making by accelerating data analysis, reducing human error, and supporting evidence-based choices. A quantitative survey of 92 companies across multiple industries examines how AI adoption influences manager…
  arxiv Ernest Górka, Dariusz Baran, Gabriela Wojak, Michał Ćwiąkała 等 2025-11-26T14:45:16Z 置信度 0.78 cs.CYcs.AIecon.GN
• Improving Urban Mobility: using artificial intelligence and new technologies to connect supply and demand
  As the demand for mobility in our society seems to increase, the various issues centered on urban mobility are among those that worry most city inhabitants in this planet. For instance, how to go from A to B in an efficient (but also less stressful) way? These…
  arxiv Ana L. C. Bazzan 2022-03-18T14:37:33Z 置信度 0.78 cs.CYcs.AIcs.LG
• Artificial Intelligence and the Generative Science of Food Formulation
  Food formulation requires balancing taste, nutrition, sustainability, and cost. Traditionally, new foods have emerged through empirical experimentation, expert intuition, and iterative refinement. Now, artificial intelligence offers the opportunity to accelera…
  arxiv Vahidullah Tac, Ellen Kuhl 2026-07-10T15:36:21Z 置信度 0.78 cs.CE
• Advances of Artificial Intelligence in Classical and Novel Spectroscopy-Based Approaches for Cancer Diagnostics. A Review
  Cancer is one of the leading causes of death worldwide. Fast and safe early-stage, pre- and intra-operative diagnostics can significantly contribute to successful cancer identification and treatment. Artificial intelligence has played an increasing role in the…
  arxiv Marina Zajnulina 2022-08-08T09:39:36Z 置信度 0.78 q-bio.TOeess.IVstat.APstat.ML
• Artificial Intelligence for Biomedical Video Generation
  As a prominent subfield of Artificial Intelligence Generated Content (AIGC), video generation has achieved notable advancements in recent years. The introduction of Sora-alike models represents a pivotal breakthrough in video generation technologies, significa…
  arxiv Linyuan Li, Jianing Qiu, Anujit Saha, Lin Li 等 2024-11-12T08:05:58Z 置信度 0.78 cs.CV
• Diffusion Models for Generative Artificial Intelligence: An Introduction for Applied Mathematicians
  Generative artificial intelligence (AI) refers to algorithms that create synthetic but realistic output. Diffusion models currently offer state of the art performance in generative AI for images. They also form a key component in more general tools, including …
  arxiv Catherine F. Higham, Desmond J. Higham, Peter Grindrod 2023-12-21T20:20:52Z 置信度 0.78 cs.LGcs.AI
• Data Work in Egypt: Who Are the Workers Behind Artificial Intelligence?
  The report highlights the role of Egyptian data workers in the global value chains of Artificial Intelligence (AI). These workers generate and annotate data for machine learning, check outputs, and they connect with overseas AI producers via international digi…
  arxiv Myriam Raymond, Lucy Neveux, Antonio A. Casilli, Paola Tubaro 2025-12-22T10:03:45Z 置信度 0.78 cs.CYcs.AI
• Use of What-if Scenarios to Help Explain Artificial Intelligence Models for Neonatal Health
  Early detection of intrapartum risks enables timely interventions to prevent or mitigate adverse labor outcomes such as cerebral palsy. However, accurate automated systems to support clinical decision-making during delivery are currently lacking. To address th…
  arxiv Abdullah Mamun, Lawrence D. Devoe, Mark I. Evans, David W. Britt 等 2024-10-12T20:21:00Z 置信度 0.78 cs.LGcs.AI
• GenAI Against Humanity: Nefarious Applications of Generative Artificial Intelligence and Large Language Models
  Generative Artificial Intelligence (GenAI) and Large Language Models (LLMs) are marvels of technology; celebrated for their prowess in natural language processing and multimodal content generation, they promise a transformative future. But as with all powerful…
  arxiv Emilio Ferrara 2023-10-01T17:25:56Z 置信度 0.78 cs.CYcs.AIcs.CLcs.HC
• Memory Based Machine Intelligence Techniques in VLSI hardware
  We briefly introduce the memory based approaches to emulate machine intelligence in VLSI hardware, describing the challenges and advantages. Implementation of artificial intelligence techniques in VLSI hardware is a practical and difficult problem. Deep archit…
  arxiv Alex Pappachen James 2012-01-28T13:38:08Z 置信度 0.78 cs.AIcs.RO
• Anvendelse av kunstig intelligens (KI) i Norge i norsk offentlig sektor 2024
  There are great expectations for the use of AI in Norway. On the other hand, it is reported that the adoption of AI in Norway is slower than expected in both the private and public sectors. Using responses from NOKIOS Technology Radar 2017-2021, IT in Practice…
  arxiv John Krogstie 2024-12-26T16:28:49Z 置信度 0.78 cs.CY
• Feature selection intelligent algorithm with mutual information and steepest ascent strategy
  Remote sensing is a higher technology to produce knowledge for data mining applications. In principle hyperspectral images (HSIs) is a remote sensing tool that provides precise classification of regions. The HSI contains more than a hundred of images of the gr…
  arxiv Elkebir Sarhrouni, Ahmed Hammouch, Driss Aboutajdine 2022-10-21T23:15:42Z 置信度 0.78 cs.CVcs.AI
• Towards Collective Intelligence: Uncertainty-aware SAM Adaptation for Ambiguous Medical Image Segmentation
  Collective intelligence from multiple medical experts consistently surpasses individual expertise in clinical diagnosis, particularly for ambiguous medical image segmentation tasks involving unclear tissue boundaries or pathological variations. The Segment Any…
  arxiv Mingzhou Jiang, Jiaying Zhou, Junde Wu, Tianyang Wang 等 2024-03-16T14:11:54Z 置信度 0.78 eess.IVcs.CV
• A Model-Based, Decision-Theoretic Perspective on Automated Cyber Response
  Cyber-attacks can occur at machine speeds that are far too fast for human-in-the-loop (or sometimes on-the-loop) decision making to be a viable option. Although human inputs are still important, a defensive Artificial Intelligence (AI) system must have conside…
  arxiv Lashon B. Booker, Scott A. Musman 2020-02-20T15:30:59Z 置信度 0.78 cs.AI
• Artificial Intelligence for Technical Debt Management in Software Development
  Technical debt is a well-known challenge in software development, and its negative impact on software quality, maintainability, and performance is widely recognized. In recent years, artificial intelligence (AI) has proven to be a promising approach to assist …
  arxiv Srinivas Babu Pandi, Samia A. Binta, Savita Kaushal 2023-06-16T21:59:22Z 置信度 0.78 cs.SEcs.AI
• Research Paradigm of Materials Science Tetrahedra with Artificial Intelligence
  The classical material tetrahedron that represents the Structure-Property-Processing-Performance-Characterization relationship is the most important research paradigm in materials science so far. It has served as a protocol to guide experiments, modeling, and …
  arxiv Shiyun Zhang, Yibo Yao, Haoquan Long, Dingwen Tao 等 2026-03-14T04:30:03Z 置信度 0.78 cond-mat.mtrl-scics.AI
• Stochastic Constraint Optimization using Propagation on Ordered Binary Decision Diagrams
  A number of problems in relational Artificial Intelligence can be viewed as Stochastic Constraint Optimization Problems (SCOPs). These are constraint optimization problems that involve objectives or constraints with a stochastic component. Building on the rece…
  arxiv Anna L. D. Latour, Behrouz Babaki, Siegfried Nijssen 2018-07-03T10:58:38Z 置信度 0.78 cs.AI
• Virtual Reality for Understanding Artificial-Intelligence-driven Scientific Discovery with an Application in Quantum Optics
  Generative Artificial Intelligence (AI) models can propose solutions to scientific problems beyond human capability. To truly make conceptual contributions, researchers need to be capable of understanding the AI-generated structures and extracting the underlyi…
  arxiv Philipp Schmidt, Sören Arlt, Carlos Ruiz-Gonzalez, Xuemei Gu 等 2024-02-20T17:48:01Z 置信度 0.78 cs.HCcs.AIcs.GRquant-ph
• Designing an Interdisciplinary Artificial Intelligence Curriculum for Engineering: Evaluation and Insights from Experts
  As Artificial Intelligence (AI) increasingly impacts professional practice, there is a growing need to AI-related competencies into higher education curricula. However, research on the implementation of AI education within study programs remains limited and re…
  arxiv Johannes Schleiss, Anke Manukjan, Michelle Ines Bieber, Sebastian Lang 等 2025-08-18T19:20:05Z 置信度 0.78 cs.CYcs.AI
• Uncertainty quantification in medical image segmentation with normalizing flows
  Medical image segmentation is inherently an ambiguous task due to factors such as partial volumes and variations in anatomical definitions. While in most cases the segmentation uncertainty is around the border of structures of interest, there can also be consi…
  arxiv Raghavendra Selvan, Frederik Faye, Jon Middleton, Akshay Pai 2020-06-04T07:56:46Z 置信度 0.78 stat.MLcs.CVcs.LG
• Astrobiology in the Time of Artificial Intelligence
  The Viking missions showcased multiple spaceflight technologies representing state-of-the-art capabilities: from digital line-scan imaging to the operation of complex onboard laboratories and software-controlled process autonomy. Since Viking, there have been …
  arxiv Caleb Scharf 2026-06-22T18:44:25Z 置信度 0.78 astro-ph.IMastro-ph.EPphysics.data-an
• On scientific understanding with artificial intelligence
  Imagine an oracle that correctly predicts the outcome of every particle physics experiment, the products of every chemical reaction, or the function of every protein. Such an oracle would revolutionize science and technology as we know them. However, as scient…
  arxiv Mario Krenn, Robert Pollice, Si Yue Guo, Matteo Aldeghi 等 2022-04-04T13:45:13Z 置信度 0.78 cs.CYcs.LGphysics.chem-ph
• Artificial Intelligence in Ovarian Cancer Histopathology: A Systematic Review
  Purpose - To characterise and assess the quality of published research evaluating artificial intelligence (AI) methods for ovarian cancer diagnosis or prognosis using histopathology data. Methods - A search of PubMed, Scopus, Web of Science, CENTRAL, and WHO-I…
  arxiv Jack Breen, Katie Allen, Kieran Zucker, Pratik Adusumilli 等 2023-03-31T12:26:29Z 置信度 0.78 eess.IVcs.AIcs.LG
• (Ir)rationality in AI: State of the Art, Research Challenges and Open Questions
  The concept of rationality is central to the field of artificial intelligence (AI). Whether we are seeking to simulate human reasoning, or trying to achieve bounded optimality, our goal is generally to make artificial agents as rational as possible. Despite th…
  arxiv Olivia Macmillan-Scott, Mirco Musolesi 2023-11-28T19:01:09Z 置信度 0.78 cs.AIcs.CYcs.HCcs.LGcs.MA
• Explainable Graph Representation Learning via Graph Pattern Analysis
  Explainable artificial intelligence (XAI) is an important area in the AI community, and interpretability is crucial for building robust and trustworthy AI models. While previous work has explored model-level and instance-level explainable graph learning, there…
  arxiv Xudong Wang, Ziheng Sun, Chris Ding, Jicong Fan 2025-12-04T07:25:01Z 置信度 0.78 cs.LG
• Multi-stakeholder Perspective on Responsible Artificial Intelligence and Acceptability in Education
  This study investigates the acceptability of different artificial intelligence (AI) applications in education from a multi-stakeholder perspective, including students, teachers, and parents. Acknowledging the transformative potential of AI in education, it add…
  arxiv A. J. Karran, P. Charland, J-T. Martineau, A. Ortiz de Guinea Lopez de Arana 等 2024-02-22T23:59:59Z 置信度 0.78 cs.CYcs.AIcs.HC
• Learning to Generate and Evaluate Fact-checking Explanations with Transformers
  In an era increasingly dominated by digital platforms, the spread of misinformation poses a significant challenge, highlighting the need for solutions capable of assessing information veracity. Our research contributes to the field of Explainable Artificial An…
  arxiv Darius Feher, Abdullah Khered, Hao Zhang, Riza Batista-Navarro 等 2024-10-21T06:22:51Z 置信度 0.78 cs.CLcs.AIcs.HC
• Trust and Medical AI: The challenges we face and the expertise needed to overcome them
  Artificial intelligence (AI) is increasingly of tremendous interest in the medical field. However, failures of medical AI could have serious consequences for both clinical outcomes and the patient experience. These consequences could erode public trust in AI, …
  arxiv Thomas P. Quinn, Manisha Senadeera, Stephan Jacobs, Simon Coghlan 等 2020-08-18T04:17:58Z 置信度 0.78 cs.AIcs.CY
• Quantum Artificial Intelligence for Secure Autonomous Vehicle Navigation: An Architectural Proposal
  Navigation is a very crucial aspect of autonomous vehicle ecosystem which heavily relies on collecting and processing large amounts of data in various states and taking a confident and safe decision to define the next vehicle maneuver. In this paper, we propos…
  arxiv Hemanth Kannamarlapudi, Sowmya Chintalapudi 2025-06-19T03:45:49Z 置信度 0.78 cs.ETcs.AIcs.ROquant-ph
• CrySPAI: A new Crystal Structure Prediction Software Based on Artificial Intelligence
  Crystal structure predictions based on the combination of first-principles calculations and machine learning have achieved significant success in materials science. However, most of these approaches are limited to predicting specific systems, which hinders the…
  arxiv Zongguo Wang, Ziyi Chen, Yang Yuan, Yangang Wang 2025-01-27T07:53:06Z 置信度 0.78 cond-mat.mtrl-scics.AI
• Prognosis of COVID-19 using Artificial Intelligence: A Systematic Review and Meta-analysis
  Purpose: Artificial intelligence (AI) techniques have been extensively utilized for diagnosing and prognosis of several diseases in recent years. This study identifies, appraises and synthesizes published studies on the use of AI for the prognosis of COVID-19.…
  arxiv SaeedReza Motamedian, Sadra Mohaghegh, Elham Babadi Oregani, Mahrsa Amjadi 等 2024-08-01T00:33:32Z 置信度 0.78 physics.med-phcs.AIcs.LG
• Strategies for Optimizing End-to-End Artificial Intelligence Pipelines on Intel Xeon Processors
  End-to-end (E2E) artificial intelligence (AI) pipelines are composed of several stages including data preprocessing, data ingestion, defining and training the model, hyperparameter optimization, deployment, inference, postprocessing, followed by downstream ana…
  arxiv Meena Arunachalam, Vrushabh Sanghavi, Yi A Yao, Yi A Zhou 等 2022-11-01T05:45:04Z 置信度 0.78 cs.LGcs.AIcs.CVcs.DCcs.NE
• Vulcan: Retreading a Tired Hypothesis with the 2024 Total Solar Eclipse
  The number of planets in the solar system over the last three centuries has, perhaps surprisingly, been less of a fixed value than one would think it should be. In this paper, we look at the specific case of Vulcan, which was both a planet before Pluto was a p…
  arxiv Michael B. Lund 2024-03-29T16:49:54Z 置信度 0.78 astro-ph.EPphysics.pop-ph
• Mapping Public Perception of Artificial Intelligence: Expectations, Risk-Benefit Tradeoffs, and Value As Determinants for Societal Acceptance
  Understanding public perception of artificial intelligence (AI) and the tradeoffs between potential risks and benefits is crucial, as these perceptions might shape policy decisions, influence innovation trajectories for successful market strategies, and determ…
  arxiv Philipp Brauner, Felix Glawe, Gian Luca Liehner, Luisa Vervier 等 2024-11-28T20:03:01Z 置信度 0.78 cs.CYcs.AIcs.HC
• Creating Scalable AGI: the Open General Intelligence Framework
  Recent advancements in Artificial Intelligence (AI), particularly with Large Language Models (LLMs), have led to significant progress in narrow tasks such as image classification, language translation, coding, and writing. However, these models face limitation…
  arxiv Daniel A. Dollinger, Michael Singleton 2024-11-24T13:17:53Z 置信度 0.78 cs.AI
• Decentralized Online Learning in General-Sum Stackelberg Games
  We study an online learning problem in general-sum Stackelberg games, where players act in a decentralized and strategic manner. We study two settings depending on the type of information for the follower: (1) the limited information setting where the follower…
  arxiv Yaolong Yu, Haipeng Chen 2024-05-06T04:35:01Z 置信度 0.78 cs.LG
• A proposal for ethically traceable artificial intelligence
  Although the problem of a critique of robotic behavior in near-unanimous agreement to human norms seems intractable, a starting point of such an ambition is a framework of the collection of knowledge a priori and experience a posteriori categorized as a set of…
  arxiv Christopher A. Tucker 2017-03-06T14:54:19Z 置信度 0.78 cs.AI
• Introduction to the SP theory of intelligence
  This article provides a brief introduction to the "Theory of Intelligence" and its realisation in the "SP Computer Model". The overall goal of the SP programme of research, in accordance with long-established principles in science, has been the simplification …
  arxiv J Gerard Wolff 2018-02-24T17:25:43Z 置信度 0.78 cs.AI
• The Need for Ethical, Responsible, and Trustworthy Artificial Intelligence for Environmental Sciences
  Given the growing use of Artificial Intelligence (AI) and machine learning (ML) methods across all aspects of environmental sciences, it is imperative that we initiate a discussion about the ethical and responsible use of AI. In fact, much can be learned from …
  arxiv Amy McGovern, Imme Ebert-Uphoff, David John Gagne, Ann Bostrom 2021-12-15T19:57:38Z 置信度 0.78 cs.CYcs.AIcs.LG
• Artificial intelligence can persuade people to take political actions
  There is substantial concern about the ability of advanced artificial intelligence to influence people's behaviour. A rapidly growing body of research has found that AI can produce large persuasive effects on people's attitudes, but whether AI can persuade peo…
  arxiv Kobi Hackenburg, Luke Hewitt, Caroline Wagner, Ben M. Tappin 等 2026-04-10T10:34:49Z 置信度 0.78 cs.CYcs.AIcs.HC
• The Future of Food: How Artificial Intelligence is Transforming Food Manufacturing
  Artificial intelligence is accelerating a new era of food innovation, connecting data from farm to consumer to improve formulation, processing, and health outcomes. Recent advances in deep learning, natural language processing, and multi-omics integration make…
  arxiv Xu Zhou, Ivor Prado, AIFPDS participants, Ilias Tagkopoulos 2025-11-17T20:17:55Z 置信度 0.78 cs.CYcs.AI
• Explainable, Interpretable & Trustworthy AI for Intelligent Digital Twin: Case Study on Remaining Useful Life
  Artificial intelligence (AI) and Machine learning (ML) are increasingly used in energy and engineering systems, but these models must be fair, unbiased, and explainable. It is critical to have confidence in AI's trustworthiness. ML techniques have been useful …
  arxiv Kazuma Kobayashi, Syed Bahauddin Alam 2023-01-17T03:17:07Z 置信度 0.78 cs.LGstat.APstat.CO
• CGraph: Graph Based Extensible Predictive Domain Threat Intelligence Platform
  Ability to effectively investigate indicators of compromise and associated network resources involved in cyber attacks is paramount not only to identify affected network resources but also to detect related malicious resources. Today, most of the cyber threat …
  arxiv Wathsara Daluwatta, Ravindu De Silva, Sanduni Kariyawasam, Mohamed Nabeel 等 2022-02-16T06:28:07Z 置信度 0.78 cs.CR
• Using GPT Models for Qualitative and Quantitative News Analytics in the 2024 US Presidental Election Process
  The paper considers an approach of using Google Search API and GPT-4o model for qualitative and quantitative analyses of news through retrieval-augmented generation (RAG). This approach was applied to analyze news about the 2024 US presidential election proces…
  arxiv Bohdan M. Pavlyshenko 2024-10-21T11:02:18Z 置信度 0.78 cs.CLcs.AIcs.IRcs.LG
• A call for embodied AI
  We propose Embodied AI as the next fundamental step in the pursuit of Artificial General Intelligence, juxtaposing it against current AI advancements, particularly Large Language Models. We traverse the evolution of the embodiment concept across diverse fields…
  arxiv Giuseppe Paolo, Jonas Gonzalez-Billandon, Balázs Kégl 2024-02-06T09:11:20Z 置信度 0.78 cs.AI
• History of generative Artificial Intelligence (AI) chatbots: past, present, and future development
  This research provides an in-depth comprehensive review of the progress of chatbot technology over time, from the initial basic systems relying on rules to today's advanced conversational bots powered by artificial intelligence. Spanning many decades, the pape…
  arxiv Md. Al-Amin, Mohammad Shazed Ali, Abdus Salam, Arif Khan 等 2024-02-04T05:01:38Z 置信度 0.78 cs.GLcs.AIcs.CLcs.HC
• Prediction and Inference: From Models and Data to Artificial Intelligence
  In this paper we present a discussion of the basic aspects of the well-known problem of prediction and inference in physics, with specific attention to the role of models, the use of data and the application of recent developments in artificial intelligence. B…
  arxiv Luca Gammaitoni, Angelo Vulpiani 2024-10-04T06:01:55Z 置信度 0.78 physics.gen-ph
• GPT for Games: An Updated Scoping Review (2020-2024)
  Due to GPT's impressive generative capabilities, its applications in games are expanding rapidly. To offer researchers a comprehensive understanding of the current applications and identify both emerging trends and unexplored areas, this paper introduces an up…
  arxiv Daijin Yang, Erica Kleinman, Casper Harteveld 2024-11-01T02:00:25Z 置信度 0.78 cs.AI
• Artificial intelligence in orthopedic regenerative medicine: from design to clinical translational pathways.
  Orthopedic regenerative medicine (ORM) addresses musculoskeletal disorders in which effective repair requires coordinated structural reconstruction, biological repair, mechanical adaptation, and functional recovery. These processes generate heterogeneous infor…
  europepmc 2026 置信度 0.80
• A simple-to-use clinical nomogram to predict radiation esophagitis among esophageal cancer patients receiving radiotherapy: a retrospective cohort study.
  Background Moderate-to-severe acute radiation esophagitis (MSARE) is a treatment-limiting toxicity of thoracic radiotherapy (RT) in esophageal cancer (EC). Early identification of high-risk patients is essential to individualize supportive care and preserve tr…
  europepmc 2026 置信度 0.80
• Machine learning in bleeding risk assessment for low-molecular-weight heparin or fondaparinux: a predictive model study.
  Backgroud No universally accepted model exists for predicting bleeding risk in patients receiving low-molecular-weight heparin or fondaparinux. Objective This study leveraged seven machine learning algorithms to build a short-term bleeding risk prediction plat…
  europepmc 2026 置信度 0.80
• Classifying voice disorders for machine learning: a pilot study using the USVAC-C2025 diagnostic framework.
  Introduction Machine learning for voice disorders relies heavily on accurate diagnostic classification, yet progress has been limited by inconsistent labelling and the absence of a reproducible framework suitable for clinical and computational use. This study …
  europepmc 2026 置信度 0.80
• Interpretable Machine Learning Analysis of Factors Associated with Postoperative Hemoglobin Reduction After Total Knee Arthroplasty: A Standardized-Protocol Cohort Study in Non-Transfused Patients.
  Background: Postoperative hemoglobin (Hb) reduction reflects the physiologic extent of perioperative blood loss after total knee arthroplasty (TKA). Whereas previous studies have relied on transfusion as a binary endpoint, transfusion decisions are highly vari…
  europepmc 2026 置信度 0.80
• Leveraging machine learning models to forecast pediatric allergic rhinitis exacerbation risk based on environmental exposure data.
  Objective Acute exacerbations of pediatric allergic rhinitis (AR) are difficult to anticipate, and individualized risk tools integrating clinical and environmental data are lacking. We developed an interpretable machine-learning model to predict 90-day AR exac…
  europepmc 2026 置信度 0.80
• Optimization of hospitalization duration and cost structure for chronic schizophrenia patients in psychiatric hospitals.
  Objective Chronic schizophrenia patients in psychiatric hospitals often have prolonged stays, high insurance resource consumption, and low efficiency. Studies quantifying the joint optimization of payment and operational efficiency are lacking, complicating th…
  europepmc 2026 置信度 0.80
• Predictive value of bronchoalveolar lavage fluid leukotriene C4 for airway hyperresponsiveness in children with <i>Mycoplasma pneumoniae</i> pneumonia: a machine learning-based study.
  Background Airway hyperresponsiveness (AHR) is a frequent sequela after acute Mycoplasma pneumoniae pneumonia (MPP) in children. This study assessed the association between bronchoalveolar lavage fluid (BALF) leukotriene C4 (LTC4) and MPP, evaluated its predic…
  europepmc 2026 置信度 0.80
• Systemic inflammatory biomarkers (NLR, SII, PNI and FPR) combined with CEA for predicting advanced colorectal neoplasms: development and temporal validation of a machine learning model.
  Background Chronic systemic inflammation is closely associated with the initiation and development of colorectal tumors. Biomarkers reflecting inflammatory status may help detect advanced colorectal neoplasms (ACRN), which include advanced adenoma and colorect…
  europepmc 2026 置信度 0.80
• Machine learning-enabled prediction of ART pregnancy outcomes: a systematic review and meta-analysis.
  Objective To systematically evaluate the diagnostic accuracy and methodological quality of machine learning (ML) prediction models for pregnancy outcomes after assisted reproductive technology (ART). Methods PubMed, Embase, the Cochrane Library, IEEE Xplore, M…
  europepmc 2026 置信度 0.80
• Electrophysiological Signatures of Sarcopenia: A Systematic Review of sEMG Features, Fatigue Indices and AI-Based Classifiers.
  Age-related sarcopenia involves structural and functional neuromuscular changes. Electrophysiological measures from surface electromyography (sEMG) capture activation dynamics, spectral fatigue indices and motor unit properties that may constitute objective si…
  europepmc 2026 置信度 0.80
• Interpretable Deep Learning Radiomics for Differentiating Pleomorphic Adenoma and Warthin Tumor.
  Background/aim Preoperative differentiation between pleomorphic adenoma (PA) and Warthin tumor (WT) is essential for optimizing surgical strategies. This study aimed to develop and validate an interpretable machine learning framework integrating clinical data,…
  europepmc 2026 置信度 0.80
• A machine learning-based screening tool for classifying post-traumatic stress disorder in firefighters: Firefighter Latent Risk Evaluation (FLARE).
  Background The prevalence of post-traumatic stress disorder (PTSD) among South Korean firefighters is likely to be under-reported because of stigma and defensive attitudes. We aimed to develop a machine learning-based classification model, named Firefighter PT…
  europepmc 2026 置信度 0.80
• Construction and validation of a machine learning-based model for predicting pneumonia risk in patients with hemorrhagic stroke.
  Objective This study aimed to develop and validate a distinct, stable, and interpretable predictive model using machine learning techniques to identify individuals at high risk of pneumonia early after admission. The goal was to provide a potential quantitativ…
  europepmc 2026 置信度 0.80
• Machine learning-based prediction of bronchiolitis in children under two years: a multicenter study within a single metropolitan area.
  Background Bronchiolitis is a leading cause of hospitalization in infants, yet early and accurate risk prediction remains a clinical challenge. Traditional models often lack the complexity to capture nonlinear interactions or the transparency required for clin…
  europepmc 2026 置信度 0.80
• Advancing In-Context Learning for Efficient and Stable Medical Report Generation.
  Vision-language models (VLMs) have shown strong generalization across multimodal tasks, but adapting them to medical report generation (MRG) often demands extensive paired image-text data that are limited due to data privacy and annotation cost. In-context lea…
  europepmc 2026 置信度 0.80
• Development and validation of a machine learning model for colorectal cancer status classification using NHANES data: A cross-sectional study.
  Colorectal cancer (CRC) is a leading cause of cancer-related morbidity and mortality worldwide. Tools based on routinely collected variables may help identify prevalent CRC status and support clinical evaluation. Traditional approaches often rely on limited pr…
  europepmc 2026 置信度 0.80
• Development and External Validation of an Explainable Machine-Learning Model for Predicting Postoperative Pulmonary Complications in Older Adults Undergoing Degenerative Spine Surgery.
  Background : Postoperative pulmonary complications (PPCs) remain common in older adults undergoing degenerative spine surgery and are associated with adverse outcomes. We aimed to develop and externally validate an explainable machine-learning model using rout…
  europepmc 2026 置信度 0.80
• Development and validation of a machine learning model for sperm DNA fragmentation rate in infertile men: a multicenter retrospective study.
  Background The sperm DNA fragmentation index (DFI) provides important reference for evaluating male fertility and assisted reproductive outcomes, and its degree of damage is influenced by multiple factors. Our study aims to develop a machine learning-based pre…
  europepmc 2026 置信度 0.80
• Integrated Intratumoral and Peritumoral Ultrasound Radiomics Models for Breast Nodule Diagnosis Using Machine Learning.
  Aims/background The differentiation of benign and malignant breast nodules, particularly those categorized as Breast Imaging Reporting and Data System (BI-RADS) 3-4, remains a clinical challenge due to the subjectivity and operator dependence of conventional u…
  europepmc 2026 置信度 0.80
• Perioperative prediction of adnexal malignancy by an interpretable machine learning model for guiding ovarian preservation in premenopausal endometrial cancer.
  Background Ovarian preservation in premenopausal patients with endometrial cancer remains challenging due to the potential presence of concurrent adnexal malignancy. To support surgical decision-making, we developed an interpretable machine learning model for …
  europepmc 2026 置信度 0.80
• Analysis of health anxiety trajectories in rabies exposure patients based on machine learning.
  Objective To identify the dynamic evolution trajectory of health anxiety in patients with initial rabies exposure and to conduct predictive analysis of health anxiety trajectories using machine learning algorithms. Methods A total of 548 rabies exposure patien…
  europepmc 2026 置信度 0.80
• Prediction and mechanistic insights into drug-induced reproductive toxicity through integrated machine learning, FAERS-based signal comparison, and network toxicology analyses.
  Drug-induced reproductive toxicity is a critical concern in drug safety evaluation, whereas conventional assessment methods are often constrained by high costs and long experimental cycles. In this study, a machine learning-based predictive model for reproduct…
  europepmc 2026 置信度 0.80
• Using Machine Learning to Predict Breast Cancer-Related Lymphedema Following Axillary Lymph Node Dissection.
  Background Breast cancer-related lymphedema (BCRL) is a common and debilitating sequela of axillary lymph node dissection (ALND). Although machine learning (ML)-based prediction models have been proposed, few focus exclusively on patients undergoing ALND, and …
  europepmc 2026 置信度 0.80
• Machine Learning Applications for Opioid Use Management in Chronic Cancer Pain: A Systematic Scoping Review.
  Chronic pain remains a critical clinical issue worldwide, with adverse effects on the quality of life of oncology patients. Meanwhile, the overuse of opioids to treat or alleviate chronic cancer pain has contributed to a global opioid crisis. The increasing ac…
  europepmc 2026 置信度 0.80
• Global trends and hotspots of machine learning in the diagnosis of prostate cancer: a bibliometric analysis from 1997 to 2024
  Purpose Prostate cancer (PCa) diagnosis has advanced with the integration of machine learning (ML). This study analyzes global trends in ML-based PCa diagnosis research using bibliometric methods. Methods A systematic search was conducted in the Web of Science…
  europepmc 2026 置信度 0.80
• Development and validation of an interpretable machine learning model for predicting systemic inflammatory response syndrome after percutaneous nephrolithotomy: A multicenter study.
  Background Systemic inflammatory response syndrome (SIRS) is a common and potentially reversible early infectious complication after percutaneous nephrolithotomy (PCNL). Accurate perioperative risk stratification may enable timely intervention; however, existi…
  europepmc 2026 置信度 0.80
• Machine learning models in post-stroke aphasia: a scoping review.
  Objective To systematically review the literature on the application of machine learning models in post-stroke aphasia, and to provide a reference for the construction and clinical application of related models. Methods Based on scoping review methodology, we …
  europepmc 2026 置信度 0.80
• Predicting Outcomes of Traumatic Brain Injury Using Machine Learning Models Among Patients at Kilimanjaro Christian Medical Centre, Tanzania: A Registry-Based Cohort Study.
  Background Traumatic brain injury (TBI) remains a major global health burden, disproportionately affecting low- and middle-income countries (LMICs) where access to neurocritical care is limited. Accurate and context-appropriate prognostic models are crucial to…
  europepmc 2026 置信度 0.80
• A Web-Based Machine Learning Calculator for Predicting Preoperative Deep Vein Thrombosis in Elderly Hip Fractures Patients.
  Purpose Hip fractures are often associated with deep vein thrombosis (DVT). This study aimed to develop machine learning models to predict preoperative DVT risk using basic clinical data from elderly patients with hip fractures. Methods Clinical data were retr…
  europepmc 2026 置信度 0.80
• Development and temporal validation of a machine learning model to estimate total MoCA scores from telephone-based items in patients with mild cognitive impairment.
  Background Periodic cognitive monitoring for mild cognitive impairment (MCI) is crucial. However, standard assessments like the Montreal Cognitive Assessment (MoCA) require in-person administration due to visual-based items, creating significant accessibility …
  europepmc 2026 置信度 0.80
• EEG-Based Seizure Prediction Approaches Within Clinically Relevant Pre-seizure Windows Using Scalp EEG Datasets: A Systematic Review.
  This systematic review synthesized evidence on EEG-based seizure prediction within clinically relevant pre-seizure windows, focusing on deep learning and machine learning models evaluated on public datasets. The review aimed to summarize predictive performance…
  europepmc 2026 置信度 0.80
• Development and validation of a routine blood test-based model to predict in-hospital postoperative pulmonary infection in older patients with hip fracture.
  Background Postoperative pulmonary infection (PPI) is a common and serious complication in older adults undergoing hip fracture surgery, leading to prolonged hospitalization, increased costs, and increased mortality. However, simple and reliable preoperative p…
  europepmc 2026 置信度 0.80
• Explainable machine learning for early prediction and anatomical classification of pulmonary embolism in the emergency department.
  Background Pulmonary thromboembolism (PTE) is a life‑threatening condition that requires prompt and accurate evaluation in the emergency department (ED). Standardized clinical scoring systems, including the Wells and revised Geneva scores, form the cornerstone…
  europepmc 2026 置信度 0.80
• Machine learning-based integrative analysis identifies CXCL13-driven tertiary lymphoid structures as favorable immune and prognostic features in osteosarcoma.
  Background Osteosarcoma, an aggressive bone malignancy with limited response to immunotherapy, remains a major clinical challenge. Tertiary lymphoid structures (TLS), as organized ectopic lymphoid aggregates, play a pivotal role in modulating antitumor immune …
  europepmc 2026 置信度 0.80
• Machine learning-driven risk prediction for post-hospitalization diabetes case management: Integrating clinical and social determinants of health.
  Objective Patients hospitalized for diabetes-related conditions face elevated risks of emergency department (ED) visits post-discharge, driven by both clinical factors and social determinants of health (SDoH). This study aimed to develop and validate predictiv…
  europepmc 2026 置信度 0.80
• Machine Learning-Based Predictive Model for Grade 3 Primary Graft Dysfunction Following Lung Transplantation: A Retrospective Cohort Study.
  Background This study aimed to identify key predictors for Grade 3 Primary Graft Dysfunction (PGD) after lung transplantation. Machine learning (ML) algorithm models were constructed for early clinical identification of high-risk PGD patients based on these pr…
  europepmc 2026 置信度 0.80
• Machine Learning Prediction of Pediatric In-Hospital Survival Before Extracorporeal Membrane Oxygenation Cannulation.
  Identifying suitable candidates for extracorporeal membrane oxygenation (ECMO) is still challenging. Our aim is to leverage machine learning (ML) to predict survival and identify critical variables influencing outcomes in pediatric patients requiring venovenou…
  europepmc 2026 置信度 0.80
• Development and validation of machine learning diagnostic models integrating clinical, CT, and laboratory features to differentiate lung cancer from pulmonary tuberculosis in patients with solitary pulmonary nodules: a single-center retrospective study.
  Background Differentiating lung cancer from pulmonary tuberculosis in patients with solitary pulmonary nodules (SPNs) remains clinically challenging, particularly in tuberculosis-endemic settings, because these two conditions may show overlapping computed tomo…
  europepmc 2026 置信度 0.80
• Machine learning to identify novel bleeding and residual thromboembolic risks in patients on anticoagulation.
  Balancing thromboembolic prevention against bleeding risk remains a key challenge during oral anticoagulant (OAC) therapy. CHA₂DS₂-VASc cannot predict residual thromboembolic risk, and HAS-BLED has insufficient predictive ability for direct oral anticoagulants…
  europepmc 2026 置信度 0.80
• Development and validation of a deep neural network for predicting coronary heart disease in hypertensive patients using 24-hour ambulatory blood pressure monitoring: a retrospective study.
  Background Coronary heart disease (CHD) remains a leading cause of morbidity and mortality worldwide. Early identification of high-risk hypertensive patients is crucial for preventing cardiovascular events. While traditional risk scores rely on static clinical…
  europepmc 2026 置信度 0.80
• Identification and Validation of an Explainable Predictive Model For Heart Failure in Patients With Hypertension.
  Background Heart failure (HF) is a heterogeneous syndrome affecting over 60 million individuals globally. Patients with hypertension are particularly susceptible to developing HF. Therefore, timely identification and predictive assessment of HF risk have signi…
  europepmc 2026 置信度 0.80
• Integrated multi-omics and functional analyses reveal a GDCA-TGR5-mediated immunometabolic signature in anorexia nervosa.
  Background Anorexia nervosa (AN) is frequently accompanied by metabolic disturbances and immune dysregulation, yet its peripheral molecular mechanisms and therapeutic targets remain poorly understood. This study integrates multi-omics analyses with experimenta…
  europepmc 2026 置信度 0.80
• AI-driven cardiovascular risk prediction in patients with diabetes: bridging algorithmic innovation to equitable clinical application.
  Machine learning models hold promise to revolutionize cardiovascular disease (CVD) prediction in patients with type 2 diabetes, with algorithms such as neural networks demonstrating superior discriminative performance in internal validations. However, a system…
  europepmc 2026 置信度 0.80
• Performance of predictive AI-based clinical decision support systems across clinical domains: A systematic review and meta-analysis.
  Despite advances in deep learning and transformer architectures, prior reviews have focused narrowly on traditional clinical decision support systems (CDSS) or single medical domains, leaving significant gaps in understanding contemporary AI-driven predictive …
  europepmc 2026 置信度 0.80
• Surgical outcomes and risk factors identification for rhegmatogenous retinal detachment repair by pneumatic retinopexy using pure air.
  Objective This study aimed to evaluate the clinical outcomes and identify risk factors for failure of pneumatic retinopexy (PR) using pure air. Methods A retrospective analysis was conducted on 199 eyes from 199 patients with uncomplicated RRD who underwent PR…
  europepmc 2026 置信度 0.80
• Developing and Validating a Machine Learning Model to Predict Brain Injury in Preterm Infants Using Multisource Data from the Early Postnatal Period.
  Background Moderate-to-severe preterm brain injury (PBI), including intraventricular hemorrhage (IVH) and periventricular leukomalacia (PVL), remains an important cause of adverse neurodevelopmental outcomes in preterm infants. Early risk stratification using …
  europepmc 2026 置信度 0.80
• Classification of malignant/benign groups in lung cancer by machine learning and investigation of feature significance of parameters.
  Objectives This study aimed to apply machine learning (ML) models to enhance lung cancer (LC) classification, distinguishing malignant from benign tumors, using data from 73 patients. Methods The dataset included PET/CT biomarkers and demographic factors, with…
  europepmc 2026 置信度 0.80
• Enhanced Survival Prediction in Head and Neck Cancer Using Convolutional Block Attention and Multimodal Data Fusion
  Accurate survival prediction in head and neck cancer (HNC) is essential for guiding clinical decision-making and optimizing treatment strategies. Traditional models, such as Cox proportional hazards, have been widely used but are limited in their ability to ha…
  datacite Farooq, Aiman, Sharma, Utkarsh, Mishra, Deepak 2024 置信度 0.66 Computer Vision and Pattern Recognition (cs.CV)FOS: Computer and information sciencesFOS: Computer and information sciences
• MeSH2Wikidata: A set of tools for the interaction between MeSH keywords, OBO Foundry, and Wikidata for enriching biomedical knowledge
  The work consists of tools for the interaction between Wikidata and OBO Foundry and source codes for the use of MeSH keywords of PubMed publications for the enrichment of biomedical knowledge in Wikidata. This work is funded by the Adapting Wikidata to support…
  datacite Turki, Houcemeddine, Chebil, Khalil, Dossou, Bonaventure, Emezue, Chris 等 2023 置信度 0.66 Knowledge and information managementInformation modelling, management and ontologiesInformation systems organisation and managementInformation retrieval and web searchData mining and knowledge discovery
• Slicing Through Bias: Explaining Performance Gaps in Medical Image Analysis using Slice Discovery Methods
  Machine learning models have achieved high overall accuracy in medical image analysis. However, performance disparities on specific patient groups pose challenges to their clinical utility, safety, and fairness. This can affect known patient groups - such as t…
  datacite Olesen, Vincent, Weng, Nina, Feragen, Aasa, Petersen, Eike 2024 置信度 0.66 Machine Learning (cs.LG)Artificial Intelligence (cs.AI)Computer Vision and Pattern Recognition (cs.CV)Computers and Society (cs.CY)FOS: Computer and information sciences
• Grand Challenge: Head and Neck Tumor Segmentation for MR-Guided Applications (HNTS-MRG) 2024
  The Head and Neck Tumor Segmentation for MR-Guided Applications (HNTS-MRG) 2024 Grand Challenge is a 2024 MICCAI Grand Challenge. PI Fuller presented the keynote virtually and in-person on 2024-10-17T0900, describing the relevant issues in biomedical image seg…
  datacite Fuller, Clifton D. 2024 置信度 0.66 Radiology and organ imagingBiomedical imagingComputational imagingArtificial intelligence not elsewhere classifiedMachine learning not elsewhere classified
• The Phantom EEG Dataset
  When you use this dataset, please cite this paper. More information about this dataset could also be found in this paper. Xu, X., Wang, B., Xiao, B., Niu, Y., Wang, Y., Wu, X., & Chen, J. (2024). Beware of Overestimated Decoding Performance Arising from Tempor…
  datacite Anonymous 2024 置信度 0.66
• The Phantom EEG Dataset
  When you use this dataset, please cite this paper. More information about this dataset could also be found in this paper. Xu, X., Wang, B., Xiao, B., Niu, Y., Wang, Y., Wu, X., & Chen, J. (2024). Beware of Overestimated Decoding Performance Arising from Tempor…
  datacite Anonymous 2024 置信度 0.66
• The Phantom EEG Dataset
  New version on https://zenodo.org/records/13341214. When you use this dataset, please cite this paper. More information about this dataset could also be found in this paper. Xu, X., Wang, B., Xiao, B., Niu, Y., Wang, Y., Wu, X., & Chen, J. (2024). Beware of Ov…
  datacite Anonymous 2024 置信度 0.66
• CORE-BEHRT: A Carefully Optimized and Rigorously Evaluated BEHRT
  The widespread adoption of Electronic Health Records (EHR) has significantly increased the amount of available healthcare data. This has allowed models inspired by Natural Language Processing (NLP) and Computer Vision, which scale exceptionally well, to be use…
  datacite Odgaard, Mikkel, Klein, Kiril Vadimovic, Thysen, Sanne Møller, Jimenez-Solem, Espen 等 2024 置信度 0.66 Machine Learning (cs.LG)FOS: Computer and information sciencesFOS: Computer and information sciences
• Journal of Student-Scientists' Research, Vol. 6 (2024)
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• Advancing Vascular Surgery: The Role Of Artificial Intelligence And Machine Learning In Managing Carotid Stenosis
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• Machine learning applications in studying mental health among immigrants and racial and ethnic minorities: an exploratory scoping review
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  datacite Park, Khushbu Khatri, Saleem, Mohammad, Al-Garadi, Mohammed Ali, Ahmed, Abdulaziz 2024 置信度 0.66 BiotechnologyBiological Sciences not elsewhere classifiedScience Policy
• Machine learning applications in studying mental health among immigrants and racial and ethnic minorities: an exploratory scoping review
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• Single-cell transcriptomes identify patient-tailored therapies for selective co-inhibition of cancer clones
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• Single-cell transcriptomes identify patient-tailored therapies for selective co-inhibition of cancer clones
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  datacite Ianevski, Aleksandr, Nader, Kristen 2024 置信度 0.66
• Collaborative learning of common latent representations in routinely collected multivariate ICU physiological signals
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• The Impact of Technology and Digital Health on Cardiology: A Review of the Present to Reach the Future
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  What is Cholesterol Concentration and Its Relationship with PPG Signals? Cholesterol concentration refers to the total amount of cholesterol present in the blood, measured in milligrams per deciliter (mg/dL). While cholesterol is a vital fatty substance necess…
  datacite ortiz, Juan david 2024 置信度 0.66 Clinical chemistry (incl. diagnostics)
• <b>Datos_individuos</b>
  What is Cholesterol Concentration and Its Relationship with PPG Signals? Cholesterol concentration refers to the total amount of cholesterol present in the blood, measured in milligrams per deciliter (mg/dL). While cholesterol is a vital fatty substance necess…
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• Predicting Deterioration in Mild Cognitive Impairment with Survival Transformers, Extreme Gradient Boosting and Cox Proportional Hazard Modelling
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• Multi-Model Ensemble Approach for Accurate Bi-Atrial Segmentation in LGE-MRI of Atrial Fibrillation Patients
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• Train-On-Request: An On-Device Continual Learning Workflow for Adaptive Real-World Brain Machine Interfaces
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• Real-Time Machine Learning Strategies for a New Kind of Neuroscience Experiments
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• When Raw Data Prevails: Are Large Language Model Embeddings Effective in Numerical Data Representation for Medical Machine Learning Applications?
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  datacite Gao, Yanjun, Myers, Skatje, Chen, Shan, Dligach, Dmitriy 等 2024 置信度 0.66 Computation and Language (cs.CL)Artificial Intelligence (cs.AI)Machine Learning (cs.LG)FOS: Computer and information sciencesFOS: Computer and information sciences
• Evaluating the Prognostic Accuracy of Two Severity Scoring Systems in Acute Kidney Failure
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  datacite Shashank Shekhar, Preeti Sinha, Wahengbam Purnakishor Singh 2024 置信度 0.66 Acute Kidney Failure, Prognostic Accuracy, Severity Scoring Systems, Clinical Outcomes, ROC Curve Analysis
• Evaluating the Prognostic Accuracy of Two Severity Scoring Systems in Acute Kidney Failure
  Background: Acute kidney failure (AKF), a rapid loss of kidney function, poses significant morbidity and mortality risks, particularly in hospitalized and critically ill patients. Accurate prognostic tools are essential for effective clinical management and im…
  datacite Shashank Shekhar, Preeti Sinha, Wahengbam Purnakishor Singh 2024 置信度 0.66 Acute Kidney Failure, Prognostic Accuracy, Severity Scoring Systems, Clinical Outcomes, ROC Curve Analysis
• Webinars - HSI Awardee Grantsmanship
  The HSI National STEM Resource Hub is preserving its website and compiled resources for future use and reference. This entry consists of the following webinars. Webinar Summer Grantsmanship Resources. Webinar Link: https://youtu.be/YwW-lbUA4xw Dr. Ellen Carpen…
  datacite HSI National STEM Resource Hub, Serrano, Elba, Morales, Gabriela, Peterman, Jarod 等 2024 置信度 0.66
• Webinars - HSI Awardee Grantsmanship
  The HSI National STEM Resource Hub is preserving its website and compiled resources for future use and reference. This entry consists of the following webinars. Webinar Summer Grantsmanship Resources. Webinar Link: https://youtu.be/YwW-lbUA4xw Dr. Ellen Carpen…
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• Prognostic Significance of Tumor Budding in Bladder Cancer: A Call for Molecular Insights
  Dear Editor, We wish to share our insights on the critical prognostic significance of tumor budding (TB) in bladder cancer (BC) and underscore the urgent necessity for further molecular-level investigations in this domain, prompted by recent studies. Tumor bud…
  datacite Doğan, Tunay 2024 置信度 0.66
• Prognostic Significance of Tumor Budding in Bladder Cancer: A Call for Molecular Insights
  Dear Editor, We wish to share our insights on the critical prognostic significance of tumor budding (TB) in bladder cancer (BC) and underscore the urgent necessity for further molecular-level investigations in this domain, prompted by recent studies. Tumor bud…
  datacite Doğan, Tunay 2024 置信度 0.66
• Self-supervised Speech Models for Word-Level Stuttered Speech Detection
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  datacite Shih, Yi-Jen, Gkalitsiou, Zoi, Dimakis, Alexandros G., Harwath, David 2024 置信度 0.66 Audio and Speech Processing (eess.AS)Artificial Intelligence (cs.AI)Computation and Language (cs.CL)Sound (cs.SD)FOS: Electrical engineering, electronic engineering, information engineering
• Questioning AI: Promoting Decision-Making Autonomy Through Reflection
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• Multi-feature Compensatory Motion Analysis for Reaching Motions Over a Discretely Sampled Workspace
  The absence of functional arm joints, such as the wrist, in upper extremity prostheses leads to compensatory motions in the users' daily activities. Compensatory motions have been previously studied for varying task protocols and evaluation metrics. However, t…
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• Understanding eGFR Trajectories and Kidney Function Decline via Large Multimodal Models
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  datacite Li, Chih-Yuan, Wu, Jun-Ting, Hsu, Chan, Lin, Ming-Yen 等 2024 置信度 0.66 Machine Learning (cs.LG)Artificial Intelligence (cs.AI)FOS: Computer and information sciencesFOS: Computer and information sciences
• A Lesion-aware Edge-based Graph Neural Network for Predicting Language Ability in Patients with Post-stroke Aphasia
  We propose a lesion-aware graph neural network (LEGNet) to predict language ability from resting-state fMRI (rs-fMRI) connectivity in patients with post-stroke aphasia. Our model integrates three components: an edge-based learning module that encodes functiona…
  datacite Chen, Zijian, Varkanitsa, Maria, Ishwar, Prakash, Konrad, Janusz 等 2024 置信度 0.66 Machine Learning (cs.LG)Signal Processing (eess.SP)Neurons and Cognition (q-bio.NC)FOS: Computer and information sciencesFOS: Computer and information sciences
• An ExplainableFair Framework for Prediction of Substance Use Disorder Treatment Completion
  Fairness of machine learning models in healthcare has drawn increasing attention from clinicians, researchers, and even at the highest level of government. On the other hand, the importance of developing and deploying interpretable or explainable models has be…
  datacite Lucas, Mary M., Wang, Xiaoyang, Chang, Chia-Hsuan, Yang, Christopher C. 等 2024 置信度 0.66 Machine Learning (cs.LG)Computers and Society (cs.CY)FOS: Computer and information sciencesFOS: Computer and information sciences
• Research on the Load_breast_cancer data set under Multiple Machine Learning Algorithms
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• A Survey on Skin Lesion Detection and Classification using Machine Learning
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• Integrated multi-omics analysis and machine learning developed diagnostic markers and prognostic model based on Efferocytosis-associated signatures for septic cardiomyopathy
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• AI-Driven Insights: A Survey on Innovative Approach for Lung Cancer Prediction Utilizing Machine Learning and Deep Learning Methods : Lung Cancer Prediction Utilizing Machine Learning and Deep Learning Methods
  The lungs are vital for exchanging oxygen and carbon dioxide, providing oxygen to cells for energy production, and removing waste carbon dioxide from the body.They also help filter and protect the body from harmful particles and pathogens in the air.Proper lun…
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• Early Screening of Breast Cancer Using Machine Learning Algorithms: A Comparative Study
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• CoRe optimizer: an all-in-one solution for machine learning
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• Bridging efficacy and efficiency: Innovations in Shapley value estimation for model-agnostic data valuation in machine learning
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• Symbolic regression as a feature engineering method for machine and deep learning regression tasks
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• Simulation-trained machine learning models for Lorentz transmission electron microscopy
  Understanding the collective behavior of complex spin textures, such as lattices of magnetic skyrmions, is of fundamental importance for exploring and controlling the emergent ordering of these spin textures and inducing phase transitions. It is also critical …
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• Chapter 14: Dynamic Programming and Reinforcement Learning
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• Rethinking Machine Learning and Deep Learning
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• Artificial intelligence, machine learning, and deep learning
  In the modern era, we are witnessing a revolutionary transformational process where the exponential diffusion of smart and connected electronic devices fosters the emergence of disruptive services, such as Internet-of-Things (IoT), smart manufacturing, autonom…
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• Neural Networks and Deep Learning Architectures: From Basics to Advanced Implementations
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• Construction of English Translation Practice Teaching Mode Based on Deep Learning Model
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• Clustering
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• Applied Mathematics and Machine Learning
  The simultaneous availability of large datasets and high-performance computing capability in recent years has enabled the rapid development of powerful machine learning algorithms. On the one hand, state-of-the-art machine learning techniques have transformed …
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• Boosting
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• Machine Learning Applications in Electric Vehicles: A Comprehensive Overview
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• Traveling Classification Profiler towards Passport Service Optimization using Machine Learning
  The issue of passport misuse poses significant threats to both national and international security, as well as the integrity of a country's immigration system. Enhancing the effectiveness of the immigration system to detect and prevent passport misuse is cruci…
  crossref Raphael Fransiskus Manurung, Jaka Sembiring, Yoanes Bandung 2024-09-20T16:25:21Z 置信度 0.70
• A Machine Learning Approach to GDP Prediction by Analyzing Economic Indicators
  A country’s economy is important for its growth and development. A well-performed economy describes the quality living of the citizens. For assessing the health of nation’s economy the GDP performs a crucial benchmark. The country’s finished goods total value …
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• SST 2024 Machine Learning Breaker Page
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• Machine learning classification of new asteroid families members
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• Causal Economic Machine Learning (CEML)
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• New Paradigm in Financial Technology Using Machine Learning Techniques and Their Applications
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• Proceedings of the 2024 2nd International Conference on Communication Networks and Machine Learning
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• Advancements in Deep Learning
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• Applied Machine Learning for Predicting Crop Performance: A Supervised Learning Perspective
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• Determinants of Bitcoin Price: A Machine Learning Approach
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• Perceptron
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• Machine learning potential for serpentines
  Serpentines are layered hydrous magnesium silicates (MgO·SiO2·H2O) formed through serpentinization, a geochemical process that significantly alters the physical property of the mantle. They are hard to investigate experimentally and computationally due to the …
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• Innovative Strategies for Ensuring Privacy in Machine Learning Environments
  This paper presents an in-depth examination of privacy-enhancing methodologies in machine learning. It highlights the integration of federated learning with cutting-edge encryption techniques and explores how blockchain architectures contribute to data privacy…
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• Decision letter for "Quantum machine learning for image classification"
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• Upscaling hydrologic phenomena using machine learning
  Hydrologic processes in snowmelt dominated systems are traditionally measured and understood at the point scale. However, snowmelt, sublimation, and snowfall rates exhibit significant spatial variability across larger landscapes. These variations are influence…
  crossref Hannah Burdett, James R Craig 2024-07-29T00:04:25Z 置信度 0.70
• Proceedings of the 2024 7th International Conference on Signal Processing and Machine Learning
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• An Evaluation and Comparison of Machine Learning Methods for Prediction of Lubricant Film Thickness
  Lubricant film thickness is a tribological parameter that significantly impacts the performance of a tribo-system, primarily by affecting the resulting friction and wear. Measuring or predicting film thickness is therefore crucial for any hydrodynamically lubr…
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• A Novel Mechanism for Identifying Malicious and Phishing URLs Using Machine Learning Classifiers
  Phishing attacks are a straightforward method for obtaining sensitive information from unsuspecting users. The goal of phishers is to acquire critical data such as usernames, passwords, and bank account details. The threat of network information insecurity is …
  crossref V. Lokeswara Reddy, M.V. Sai Sarath Chandra 2025-02-11T18:21:27Z 置信度 0.70
• Author Index
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• Machine Learning-based Design and Optimization of High-Speed Circuits
  This book describes machine learning-based new principles, methods of design and optimization of high-speed integrated circuits.
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• Organizing Committees
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• Carbon Price Forecasting with Optimized Machine Learning Methods
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• Contents
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• Machine learning-based seismic prediction of building structures
  The impact of earthquakes on building structures is the most direct and significant aspect of earthquake disasters, and the seismic resistance of building structures is a key factor in ensuring human safety and reducing economic losses. Ground shaking caused b…
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• Reviewers: FMLDS 2024
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• Review for "Machine learning interatomic potentials for amorphous zeolitic imidazolate frameworks"
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• Machine Learning Prediction of Lightning Damage to Aircraft
  Lightning can cause physical damage to the aircraft structure, including the wings, nose cone, and other components. This damage can compromise the structural integrity of the aircraft and pose a serious risk to passenger safety. In addition, it can cause elec…
  crossref Pavlo Kochkin 2024-03-11T12:43:31Z 置信度 0.70
• Information-Driven Machine Learning
  This textbook explains the 'why' behind data science, deep learning, and machine learning, and explores a systematic approach to model engineering
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• 2024 IEEE 3rd Workshop on Machine Learning on Edge in Sensor Systems (SenSys-ML)
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• Machine learning-assisted Fourier transform infrared and Raman spectroscopic sensing in agricultural and food systems
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• Decision letter for "Quantum machine learning for image classification"
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• Leveraging Machine Learning to Enhance Injury Prevention Strategies for Fast Bowlers
  Fast bowlers in cricket face a high risk of injury due to the immense physical strain associated with their role, often resulting in prolonged absences and performance declines. This study aims to develop a predictive model for fast bowler injuries using the R…
  crossref S Pandikumar, C Menaka, Arun M 2024-10-26T11:46:02Z 置信度 0.70
• Predicting College Admission Results with Machine Learning on Unstructured Online Data
  College admissions in the U nited States is a complex and often opaque process, leading to uncertainty and potential unfair biases. This paper presents a novel approach to predicting college admission results using machine learning on unstructured online data.…
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• MLCAD 2024 Cover Page
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• Rhythmische Vorteile in Big Data und Machine Learning
  Das Buch behandelt verschiedene Aspekte der Biophysik und die hierarchische Kommunikation zwischen verschiedenen biologischen Systemen.
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• A Coherent Signal Detector Suitable for Machine Learning Applications
  Coherent signals, such as a time varying voltage appearing on a radio antenna, are fundamentally different than non-coherent signals, such as the power magnitude of an individual pixel in a CCD camera. This discussion explores the details of the differences be…
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• Review for "Machine learning interatomic potentials for amorphous zeolitic imidazolate frameworks"
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• Strong Machine Learning: a Way Towards Human-Level Intelligence
  Machine learning has achieved remarkable success with deep learning technologies. However, these methods are often inefficient in terms of resources; they require large datasets, many parameters and consume much computational power. In this paper, I define a g…
  crossref Danko Nikolic 2024-01-02T05:25:27Z 置信度 0.70
• Choosing Features for Stress Prediction with Machine Learning
  Feature selection is a crucial step in building effective machine learning models, as it directly impacts model accuracy and interpretability.Driven by the aim of improving stress prediction models, this article evaluates multiple approaches for identifying th…
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• Optimizing Renewable Energy Integration with Machine Learning for Sustainability
  Progressions in technologies for renewable energy have rendered feasible fresh avenues for energy production that is sustainable. Nonetheless, melding renewable energy sources into pre-existing power grids encounters hurdles, owing to their sporadic nature. Ma…
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• Index
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• Title Page iii
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• Front Matter
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• Copyright Page
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• Copyright
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• Using machine learning to provide understanding along with results
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• Early detection approach for analysis of osteoarthritis using artificial intelligence and machine learning
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• Frontmatter
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• Review for "Prediction of hydrogel swelling states using machine learning methods"
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  crossref Mayank Srivastava, Yajur, Sujata 2024-11-22T14:16:12Z 置信度 0.70
• Development of a Machine Learning derived Anticholinergic Burden Scale (ML-ACB scale): A Machine Learning Approach with Enhanced Drug Properties and Weighting
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  crossref Oteng Phutietsile, Nikoletta Fotaki, Prasad Nishtala 2024-10-03T06:32:12Z 置信度 0.70
• Author comment: Machine learning for stochastic parametrization — R0/PR1
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• Deep Learning Machine Vision
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• Cover
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• Preface
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• Internet of Things and Machine Learning for Type I and Type II Diabetes
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• Breast Cancer Prediction Using a Machine Learning Approach
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• Machine Learning—Automated Machine Learning (AutoML) for Disease Prediction
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• Unsupervised Anomaly Detection
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  crossref Suliman Alnutefy, Ali Alsuwayh 2024-02-04T14:25:56Z 置信度 0.70
• Speaker identification using hybrid subspace, deep learning and machine learning classifiers
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• Machine learning with sklearn
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• DDoS Detection using Machine Learning
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• Optimized Extreme Learning Machine with Bacterial Colony Optimization Algorithm for Disease Diagnosis in Clinical Datasets
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• Copyright Page
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• Index
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