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• Practical Applications of Online Machine Learning
  crossref Steffen Moritz, Florian Dumpert, Christian Jung, Thomas Bartz-Beielstein 等 2024-02-05T05:02:18Z 置信度 0.70
• Applications of Machine Learning in Medical Research
  crossref Basavarajaiah D. M., Bhamidipati Narasimha Murthy 2020-11-05T11:06:30Z 置信度 0.70
• Integration of Multimodal NLP Systems for Real-Time Clinical Decision Support in Digital Healthcare
  The Integration of Multimodal Natural Language Processing(NLP) Systems for Real-Time Clinical Decision Support System(CDSS) in Digital Healthcare, improves existing clinical decision support systems by integrating various sources of information, including real…
  crossref Karthikeyan Panneerselvam 2026-06-02T09:34:20Z 置信度 0.70
• Introduction to Artificial Intelligence and Machine Learning
  crossref Frank M. Groom 2019-11-25T08:22:46Z 置信度 0.70
• Knowledge Acquisition Via Incremental Conceptual Clustering
  crossref Douglas H. Fisher 2003-04-04T16:57:10Z 置信度 0.70
• Machine Learning for Product Design and Customization in Advanced Manufacturing Practices
  The design and development of a particular product always play an important role in the successful performance of that particular product so that it may sustain itself in the competitive market for a longer period. Machine learning has been reported as a novel…
  crossref Vinay Kumar, Nishant Ranjan 2025-10-29T15:02:02Z 置信度 0.70
• Lexical Methods for Identifying Emotions in Text Based on Machine Learning
  The study of emotions has emerged as an important area of research because of the wealth of information it can provide. Emotions can be expressed in a variety of ways including words, facial expressions, written material, and movements. Natural language proces…
  crossref Mridula Gupta 2025-02-12T11:53:51Z 置信度 0.70
• Machine Learning Applications for Anomaly Detection
  The aim of this chapter is to describe and analyze the application of machine learning for anomaly detection. The study regarding the anomaly detection is a very important thing. The various phenomena often occur related to the anomaly study, such as the occur…
  crossref Teguh Wahyono, Yaya Heryadi 2022-07-08T11:31:23Z 置信度 0.70
• Machine Learning
  Machine learning techniques have the potential of alleviating the complexity of knowledge acquisition. This book presents today’s state and development tendencies of machine learning. It is a multi-author book. Taking into account the large amount of knowledge…
  crossref 2012-03-23T15:40:22Z 置信度 0.70
• Research of unsupervised machine learning methods for data analy-sis and preparation and modern approaches to building machine learning models – automated machine learning systems
  Data preprocessing in machine learning tasks is an important step in the data mining process. To automate the data processing process and make it more suitable for the data under study, data preprocessing methods are implemented in AutoML systems. The purpose …
  crossref I.A. Popova, G.I. Afanasyev, V.B. Timofeev, Yu.E. Gapanyuk 2025-08-21T10:09:24Z 置信度 0.70
• Machine Learning in Python
  Diabetes is a disease of the modern world. The modern lifestyle has led to unhealthy eating habits causing type 2 diabetes. Machine learning has gained a lot of popularity in the recent days. It has applications in various fields and has proven to be increasin…
  crossref Astha Baranwal, Bhagyashree R. Bagwe, Vanitha M 2019-07-24T09:29:18Z 置信度 0.70
• Parasite Detection From Digital Images Using Deep Learning
  Parasitosis is a disease caused by parasites that could infect humans, animals, or plants. The parasites include mites, ascariasis, liver flukes, and malaria. The methods to detect parasites include pathological examination, immunological examination, and imag…
  crossref Yulin Zhu, Wei Qi Yan 2022-10-24T11:37:36Z 置信度 0.70
• Correction to “Predicting Ophthalmic Clinic Non‐Attendance Using Machine Learning: Development and Validation of Models Using Nationwide Data”
  crossref 2025-05-06T19:30:56Z 置信度 0.70
• Artificial Intelligence and Machine Learning Applications in Musculoskeletal Imaging
  crossref Sheila Enamandram, Emir Sandhu, Bao H. Do, Joshua J. Reicher 等 2020-05-28T18:24:23Z 置信度 0.70
• A Research Agenda
  This chapter focuses on the on cross-section of stock returns in research opportunities and related potential applications in other areas of asset pricing. It begins with empirical applications of machine learning (ML) tools, noting that part of the challenge …
  crossref Stefan Nagel 2022-05-23T12:43:40Z 置信度 0.70
• Trustworthy Machine Learning with Out-of-Distribution Data
  crossref Bo Han, Tongliang Liu 2025-10-19T19:52:18Z 置信度 0.70
• Machine Learning and Life Sciences
  crossref Shyamasree Ghosh, Rathi Dasgupta 2022-05-04T17:03:22Z 置信度 0.70
• Training a Vision Guided Mobile Robot
  crossref Gordon Wyeth 2002-12-22T04:48:21Z 置信度 0.70
• AUTOMATON
  This article displays a design ethnographic case study on an ongoing machine learning project at a Scandinavian gamification start-up company. From late 2020 until early 2021, the project produced a machine learning proof of concept, later implemented in the g…
  crossref Adam Palmquist, Isak Barbopoulos, Miralem Helmefalk 2023-01-20T15:44:01Z 置信度 0.70
• Machine Learning–Based Clinical Prediction Models in Psychopathology: Can Transfer Learning Fix the “Illusory Generalizability” Problem?
  crossref Jason Smucny 2025-09-05T15:42:43Z 置信度 0.70
• Pattern Recognition and Machine Learning
  crossref 2006-12-21T17:48:14Z 置信度 0.70
• Statistical Similarity in Machine Learning
  The main requirement for machine learning algorithms is the ability to generalize learning outcomes to new samples. This requirement is based on the compactness hypothesis, which assumes that objects belonging to the same class are located closer to each other…
  crossref Dmitriy Klyushin 2023-12-16T09:12:07Z 置信度 0.70
• Signal identification in cognitive radios using machine learning
  As an intelligent radio, cognitive radio (CR) allows the CR users to access and share the licensed spectrum. Being a typical noncooperative system, the applications of signal identification in CRs have emerged. This chapter introduces several signal identifica…
  crossref Jingwen Zhang, Fanggang Wang 2019-07-04T13:28:42Z 置信度 0.70
• Infrastructure for Machine Learning Workloads
  crossref Mohammad Reza Mahdiani 2026-04-30T22:18:03Z 置信度 0.70
• Machine Learning for Energy Analysis
  In this chapter, the authors begin by defining machine learning, discussing the different types, and introducing three common algorithms that are used for research. They then investigate the use of machine learning algorithms for energy analysis on a project c…
  crossref 2026-06-26T23:12:41Z 置信度 0.70
• Hybrid Combination of Machine Learning Techniques for Diagnosis of Liver Impairment Disease in Clinical Decision Support System
  crossref Likha Ganu, Biri Arun 2022-06-25T08:03:22Z 置信度 0.70
• Machine Learning
  crossref Achim Zielesny 2016-04-14T10:45:37Z 置信度 0.70
• Big Data Analytics Using Machine Learning Techniques for Prediction on Datasets
  Data analytics is the process of performing scientific and statistical analysis on raw data in order to transform it into information that can be used for gaining knowledge. A recently emerging trend in feature abstraction is the combination of computational t…
  crossref Ankit Verma 2023-06-05T08:19:15Z 置信度 0.70
• Fundamentals of machine learning
  crossref Yan Liang, Jeong-Yeol Yoon 2024-07-19T06:47:21Z 置信度 0.70
• Large-Scale Machine Learning for Species Distributions
  crossref 2017-09-01T11:30:37Z 置信度 0.70
• Machine Learning
  Machine learning (ML) has become a powerful tool in real-life applications including modern biology. The relationship between biology and ML has gained widespread attention in various facets of biological engineering. The chapter first introduces ML and its co…
  crossref Mohd Zafar, Ramkumar Lakshmi Narayanan, Saroj K. Meher, Shishir K. Behera 2018-09-01T00:12:43Z 置信度 0.70
• Machine Learning for Web Proxy Analytics
  Proxy servers used around the globe are typically graded and built for small businesses to large enterprises. This does not dismiss any of the current efforts to keep the general consumer of an electronic device safe from malicious websites or denying youth of…
  crossref Mark Maldonado, Ayad Barsoum 2022-07-08T11:31:23Z 置信度 0.70
• Polynomial Time Learnability of Simple Deterministic Languages
  crossref Hiroki Ishizaka 2003-04-04T16:55:36Z 置信度 0.70
• Machine learning in brain imaging genomics
  crossref J. Yan, L. Du, X. Yao, L. Shen 2016-08-19T15:32:31Z 置信度 0.70
• Tracking the Best Expert
  crossref Mark Herbster, Manfred K. Warmuth 2002-12-22T04:48:21Z 置信度 0.70
• 2022 International Conference on Machine Learning, Control, and Robotics MLCR 2022
  crossref 2023-02-08T18:58:55Z 置信度 0.70
• Credit Card Fraud Detection System using Machine Learning
  The global danger posed by credit card fraud to financial institutions and customers makes the development of strong fraud detection systems imperative. In this study, we suggest a novel method for detecting credit card fraud that makes use of Convolutional Ne…
  crossref Saurav Naik, Aarth Dahale 2024-08-16T08:58:52Z 置信度 0.70
• Fundamentals of Machine Learning
  This chapter provides a brief survey of machine learning (ML) basics and introduce its core ideas, algorithms, and applications in diverse fields as a background information for understanding its application in atomic layer deposition and thin film deposition.…
  crossref Oluwatobi Adeleke, Sina Karimzadeh, Tien-Chien Jen 2023-10-31T14:25:44Z 置信度 0.70
• Predicting the Employment Destinations of University Students Based on Machine Learning Algorithms
  The research on the classification prediction of students' employment destinations in higher education not only opens up new application areas for classification algorithms, but also represents a new attempt to introduce machine learning algorithms into the an…
  crossref 2023-02-06T05:40:40Z 置信度 0.70
• Tracking the Best Disjunction
  Littlestone developed a simple deterministic on-line learning algorithm for learning k-literal disjunctions. This algorithm (called $${WINNOW}$$ ) keeps one weight for each of then variables and does multiplicative updates to its weights. We develop a randomiz…
  crossref Peter Auer, Manfred K. Warmuth 2002-12-22T04:48:21Z 置信度 0.70
• Image-based Candlestick Pattern Classification with Machine Learning
  Financial markets, such as the stock market, bond market and foreign exchange market, are important channels for fund transfer. As a graphical analysis tool, candlestick charts use graphs to display the open, high, low, and close prices in a specific period. I…
  crossref Chenghan Xu 2021-09-06T17:42:54Z 置信度 0.70
• Multivariate Decision Trees
  crossref Carla E. Brodley, Paul E. Utgoff 2003-04-04T16:55:36Z 置信度 0.70
• Distinctive features of nonverbal behavior and mimicry in application interviews through data analysis and machine learning
  This paper reveals the characteristics and effects of nonverbal behavior and human mimicry in the context of application interviews. It discloses a novel analyzation method for psychological research by utilizing machine learning. In comparison to traditional …
  crossref Sanne Roegiers, Elias Corneillie, Filip Lievens, Frederik Anseel 等 2022-05-07T11:42:40Z 置信度 0.70
• A hybrid modeling framework for quality prediction in sheet hydroforming process: application of regression analysis and machine learning algorithm
  In recent years, the sheet hydroforming process has received widespread attention as one of the new and efficient methods in metal forming. The complexity of material behavior at different temperatures and strain rates has made the need for accurate modeling a…
  crossref Kiarash Keivan, Saeed Yaghoubi, Sayyed Roohollah Kazemi, Masoud Seidi 2026-02-27T07:55:07Z 置信度 0.70
• Comparative Analysis of Machine Learning Models in Predictive Analytics for Residential Energy Consumption
  crossref Hongyuan Jia 2024-06-12T17:41:23Z 置信度 0.70
• Machine learning approaches for image classification in developmental biology and clinical embryology
  ABSTRACT The rapid increase in the amount of available biological data together with increasing computational power and innovative new machine learning algorithms has resulted in great potential for machine learning approaches to revolutionise image analysis i…
  crossref Camilla Mapstone, Berenika Plusa 2025-02-17T11:38:11Z 置信度 0.70
• Sepsis Prediction System using Machine Learning and Deep Learning Approaches for Early Clinical Diagnosis
  Sepsis is a life-threatening medical condition caused by the body's extreme response to infection, which can lead to organ failure and death if not detected and treated early. Timely identification of sepsis remains a significant challenge in healthcare system…
  crossref K.V.Kiran K.V.Kiran, Malla Pavithra, Shaik Nazeer Babu, Suraboina Yerusha 等 2026-04-17T08:50:07Z 置信度 0.70
• Benchmarking Machine Learning and Deep Learning Models for 60-min Ahead Blood Glucose Prediction in Type 1 Diabetes with Simulated and Clinical Data
  Blood glucose (BG) management is crucial for patients with type 1 diabetes, requiring insulin dosage adjustments based on glucose levels to maintain concentrations within the target range. Accurate BG predictions provide insights into future glucose trends, en…
  crossref Zelin Shen 2026-03-24T19:45:52Z 置信度 0.70
• Transforming clinical virology with AI, machine learning and deep learning: a comprehensive review and outlook
  In the rapidly evolving field of clinical virology, technological advancements have always played a pivotal role in driving transformative changes. This comprehensive review delves into the burgeoning integration of artificial intelligence (AI), machine learni…
  crossref Abhishek Padhi, Ashwini Agarwal, Shailendra K. Saxena, C. D. S. Katoch 2023-09-21T07:01:55Z 置信度 0.70
• Reshaping Parasitology Diagnostics with Machine Learning: A Path Toward Equity in Global Health
  crossref Varol Tunali 2026-01-24T07:22:00Z 置信度 0.70
• HARNESSING MACHINE LEARNING IN HPV DIAGNOSTICS: MODEL PERFORMANCE, EXPLAINABILITY, AND CLINICAL INTEGRATION
  : Human Papillomavirus (HPV) remains a significant global health concern, contributing to cervical and oropharyngeal cancers. While traditional diagnostic methods such as PCR-based assays and cytological screenings are widely used, they present limitations in …
  crossref Bahar Senel 2025-06-28T15:30:28Z 置信度 0.70
• Novel and improved stage estimation in Parkinson's disease using clinical scales and machine learning
  crossref R. Prashanth, Sumantra Dutta Roy 2018-05-05T01:33:28Z 置信度 0.70
• Machine-Learning Classifier for Liver Disease and Periodontitis Using Biochemical and Clinical Parameters
  Introduction: The liver is vital for various physiological functions, including bile and protein synthesis necessary for digestion, nutrient metabolism, and cholesterol regulation. Periodontitis, an oral disease associated with systemic conditions like cardiov…
  crossref Pradeep Kumar, Jai Varsheni, Carlos Ardila 2026-06-02T12:54:10Z 置信度 0.70
• 2003 International Conference On Machine Learning And Cybernetics
  Conference proceedings front matter may contain various advertisements, welcome messages, committee or program information, and other miscellaneous conference information. This may in some cases also include the cover art, table of contents, copyright statemen…
  crossref 2011-06-07T13:32:59Z 置信度 0.70
• Machine Learning Environments
  You have learned about data and algorithms. Next, you will put the pieces together and build the CML model. ML environments perform a critical function. They act as an important piece of middleware, enabling you to create ML models from the data for later use …
  crossref Mark Wickham 2018-10-23T21:29:44Z 置信度 0.70
• Introduction to Machine Learning Part Two
  crossref Ton J. Cleophas, Aeilko H. Zwinderman 2013-05-29T15:06:45Z 置信度 0.70
• Malaria parasite detection using different machine learning classifier
  In the tropical and the subtropical countries, malaria has been a challenge, which really needs a quick and precise diagnosis to put a stop or control the disease. The conventional microscopy method has some shortcomings which includes time consumption and rep…
  crossref Adedeji Olugboja, Zenghui Wang 2017-11-16T21:55:05Z 置信度 0.70
• MACHINE LEARNING ALGORITHMS IN FACILITATING AND ASSISTING ROCKET DESCENT AND LANDING
  This paper presents a Unity-based reinforcement learning system for simulating rocket descent and landing. Leveraging the Unity ML-Agents framework, our approach applies Proximal Policy Optimization (PPO) combined with imitation learning to balance exploration…
  crossref Ryan Shen, Andrew Park 2025-10-30T11:16:56Z 置信度 0.70
• Diabetes Prediction Using Machine Learning
  Machine learning (ML) techniques for healthcare informatics provide health professional insight into disease development. Many healthcare topics are suitable for ML research, such as diabetes prediction and classification. Common ML approaches use a classifica…
  crossref Stephanie Tian, Guanghui Hui 2024-09-11T12:25:22Z 置信度 0.70
• QUANTUM MACHINE LEARNING OVERVIEW
  Quantum Machine Learning (QML) represents an emerging interdisciplinary field that harnesses quantum computing principles to enhance machine learning algorithms and develop quantum-native learning paradigms. This convergence exploits fundamental quantum mechan…
  crossref Sulekh Kumar, Kamla Kumari, Prbhat Purushottam, Momita Kundu 2025-09-18T06:02:56Z 置信度 0.70
• Machine learning-enabled powder-spreading process
  crossref Ramandeep Singh Sidhu, Raman Kumar 2025-01-18T22:14:46Z 置信度 0.70
• Linguistic Biomarkers of Neurological, Cognitive, and Psychiatric Disorders: Verification, Analytical Validation, Clinical Validation, and Machine Learning
  crossref 2024-08-07T05:35:13Z 置信度 0.70
• Machine Learning-Based Detection of Human Metapneumovirus (HMPV) Using Clinical Data
  Human Metapneumovirus (HMPV) is a prominent respiratory pathogen, particularly affecting children, the elderly, and immunocompromised populations.Early detection of HMPV is critical for timely intervention and improved patient outcomes; however, traditional di…
  crossref Rocco de Filippis, Abdullah Al Foysal 2025-04-11T05:54:01Z 置信度 0.70
• Machine Learning Techniques in Clinical Vision Sciences
  This review presents and discusses the contribution of machine learning techniques for diagnosis and disease monitoring in the context of clinical vision science. Many ocular diseases leading to blindness can be halted or delayed when detected and treated at i…
  crossref Miguel Caixinha, Sandrina Nunes 2016-06-30T18:34:41Z 置信度 0.70
• Machine learning: life science
  crossref 2017-05-22T13:55:19Z 置信度 0.70
• Machine learning
  This entry describes machine learning as a phenomenon.
  crossref Alina Trapova 2022-10-04T23:09:44Z 置信度 0.70
• Utilizing machine learning for predicting heart failure outcomes: A path toward developing a patient‐centered approach
  Heart failure (HF)—a global pandemic—poses a huge burden to healthcare systems, with a staggering 64.3 million people worldwide estimated to suffer from the ailment in 2017. Projections suggest a total cost of around $69.8 billion for HF by the year 2030 in th…
  crossref Rayyan Nabi, Tabeer Zahid, Hanzala A. Farooqi 2024-03-26T09:50:06Z 置信度 0.70
• Pixheart: AI-Powered Automated ECG Analysis Using Hybrid CNN-LSTM and Machine Learning Models for Clinical Diagnostics
  Working with Pixemantic and its Pixheart platform, this project introduces an AI-driven web app for automated Electrocardiogram (ECG) analysis. The system processes scanned ECG images using CNN and LSTM models to extract cardiac features to detect abnormalitie…
  crossref Mohamed Touati, Rabeb Touati, Mohamed Medimegh, Laurent Nana 等 2026-06-02T20:03:16Z 置信度 0.70
• US Food and Drug Administration Releases Artificial Intelligence/Machine Learning Action Plan
  Journal of Clinical Engineering: 4/6 2021 - Volume 46 - Issue 2 - p 54-55 doi: 10.1097/JCE.0000000000000454
  crossref 2021-03-18T15:00:47Z 置信度 0.70
• Learning to Improve Coordinated Actions in Cooperative Distributed Problem-Solving Environments
  crossref Toshiharu Sugawara, Victor Lesser 2002-12-22T05:04:10Z 置信度 0.70
• 2003 International Conference On Machine Learning And Cybernetics
  Conference proceedings front matter may contain various advertisements, welcome messages, committee or program information, and other miscellaneous conference information. This may in some cases also include the cover art, table of contents, copyright statemen…
  crossref 2011-06-07T17:32:59Z 置信度 0.70
• Machine Learning with Privacy
  crossref Patrick C. K. Hung, Sarajane Marques Peres 2022-03-25T14:52:38Z 置信度 0.70
• Proceedings 2021 3rd International Conference on Applied Machine Learning [Title page iii]
  crossref 2022-02-18T20:34:52Z 置信度 0.70
• Editorial: New Editorial Board Members
  crossref Thomas G. Dietterich 2003-04-04T16:55:36Z 置信度 0.70
• Structural Breaks in Carbon Emissions: A Machine Learning Analysis
  crossref Jiaxiong Yao, Yunhui Zhao 2026-07-15T10:55:32Z 置信度 0.70
• Robust Classification for Imprecise Environments
  crossref Foster Provost, Tom Fawcett 2002-12-22T05:54:50Z 置信度 0.70
• Machine learning assisted mid-infrared spectrochemical fibrillar collagen imaging in clinical tissues
  Abstract Significance Label-free multimodal imaging methods that can provide complementary structural and chemical information from the same sample are critical for comprehensive tissue analyses. These methods are specifically needed to study the complex tumor…
  crossref Wihan Adi, Bryan E. Rubio Perez, Yuming Liu, Sydney Runkle 等 2024-05-27T00:55:15Z 置信度 0.70
• Toward a Personal Drug Detection Assistant: Machine Learning for Detection of Synthetic Cannabinoid Receptor Agonists
  Detection of novel psychoactive substances such as synthetic cannabinoid receptor agonists (SCRAs) is a worldwide problem with serious clinical and public health implications. Rapid, low-cost, and accurate screening methods are needed but are fraught with chal…
  crossref Shannon Haymond 2022-04-21T19:14:23Z 置信度 0.70
• The effect of machine learning and artificial intelligence on the use of robots in neurosurgery
  Robotics has made rapid inroads into specialised fields of surgery like neurosurgery. The robot has many advantages like increasing accuracy, eliminating muscle fatigue and physiological tremor during long operations, all of which improve outcomes and avoid po…
  crossref Dev Bhattacharyya 2024-02-23T17:05:47Z 置信度 0.70
• Machine Learning for Natural Language Processing (and Vice Versa?)
  crossref Claire Cardie 2005-11-09T11:54:27Z 置信度 0.70
• Machine learning techniques and multi-objective programming to select the best suppliers and determine the orders
  Selection of appropriate suppliers and allocation the orders among them have become the two key strategic decisions regarding purchasing. In this study, a two-phase integrated approach is proposed for solving supplier selection and order allocation problems. P…
  crossref Asma ul Husna, Saman Hassanzadeh Amin, Ahmad Ghasempoor 2025-01-18T19:36:48Z 置信度 0.70
• Bio-Inspired Algorithms in Machine Learning and Deep Learning for Diabetes Diagnosis
  Bio Inspired algorithms in machine learning and deep learning for diabetic affects millions of individuals throughout the globe and is the leading cause of blindness in persons of working age who have diabetes. This highlights the critical need of a trustworth…
  crossref S. Aathilakshmi, S. Balasubramaniam, Ayodeji Olalekan Salau 2025-01-02T15:33:02Z 置信度 0.70
• Phase Transitions in Machine Learning
  crossref 2012-02-07T08:44:39Z 置信度 0.70
• Machine Learning in Computational Biology
  crossref 2011-08-29T12:38:13Z 置信度 0.70
• An inpatient fall risk assessment tool: Application of machine learning models on intrinsic and extrinsic risk factors
  This study aimed to identify the most impactful set of intrinsic and extrinsic fall risk factors and develop a data-driven inpatient fall risk assessment tool (FRAT). The dataset used for the study comprised in-hospital fall records from 2012 to 2017. Four mac…
  crossref Sonia Jahangiri, Masoud Abdollahi, Rasika Patil, Ehsan Rashedi 等 2023-12-08T03:01:45Z 置信度 0.70
• Enhancing Energy Efficiency With Smart Building Energy Management System Using Machine Learning and IOT
  The energy management system designed on the networking platform has been interfaced with controller to control the electrical device using the Wireless communication has been used as the most reliable and efficient technology in short-range communication. In …
  crossref M.Sahaya Sheela, S. Gopalakrishnan, I.Parvin Begum, J. Jasmine Hephzipah 等 2024-07-19T09:11:40Z 置信度 0.70
• High Performance Concrete (HPC) Compressive Strength Prediction With Advanced Machine Learning Methods
  In this chapter, the authors realized prediction applications of concrete compressive strength values via generation of various hybrid models, which are based on decision trees as main a prediction method. This was completed by using different artificial intel…
  crossref Melda Yucel, Ersin Namlı 2022-07-08T11:31:23Z 置信度 0.70
• Advanced Interpretable Machine Learning Methods for Clinical NGS Big Data of Complex Hereditary Diseases, 2nd Edition
  crossref 2021-07-01T15:54:18Z 置信度 0.70
• Stroke Risk Prediction Using Imbalance-Sensitive Machine Learning Models on Structured Clinical Data
  crossref Ayyappan G 2026-06-22T19:52:40Z 置信度 0.70
• Non-invasive Prediction of Ki-67 Status in Hepatocellular Carcinoma Using Interpretable Machine Learning with Clinical and CT Radiomics Features
  Abstract Objective : This study aims to investigate the application value of a radiomics-based machine learning model derived from CT images in the preoperative prediction of Ki-67 proliferation status in hepatocellular carcinoma (HCC). Additionally, the SHapl…
  crossref Shengzhen Dai, Xiaoyi Wang, Shishi Luo 2025-11-03T09:37:02Z 置信度 0.70
• A characteristic cerebellar biosignature for bipolar disorder, identified with fully automatic machine learning
  Abstract Backround Transcriptomic profile differences between patients with bipolar disorder and healthy controls can be identified using machine learning and can provide information about the potential role of the cerebellum in the pathogenesis of bipolar dis…
  crossref Georgios V. Thomaidis, Konstantinos Papadimitriou, Sotirios Michos, Evangelos Chartampilas 等 2022-01-23T08:40:12Z 置信度 0.70
• A Survey on Design a Machine Learning Method to Identify Skin Diseases Using Machine Learning and Image Processing
  Machine learning algorithms are being used extensively in biomedical fields for segmentation and analysis. These algorithms use features derived from images as input to make a conclusion. So, choosing proper feature extraction methods pooled with suitable Machi…
  crossref Amar S. Chandgude, Farah Haneef 2026-06-26T15:05:36Z 置信度 0.70
• Machine Learning
  crossref 2022-06-24T09:07:23Z 置信度 0.70
• Causal Machine Learning
  This seminar provides an in-depth exploration of causal machine learning, equipping participants with sophisticated techniques to differentiate causation from correlation using modern machine learning tools integrated with robust econometric methods. By introd…
  crossref Melvyn Weeks 2025-09-14T10:11:44Z 置信度 0.70
• Figure 4: The machine learning algorithms.
  crossref 2024-05-14T03:56:27Z 置信度 0.70
• A Review of the Fourth International Workshop on Machine Learning
  crossref Rogers P. Hall, Brian Falkenhainer, Nicholas Flann, Steve Hampson 等 2003-04-04T16:57:10Z 置信度 0.70
• Basics of Machine Learning
  crossref Yu Geng, Qin Li, Geng Yang, Wan Qiu 2024-08-29T20:24:55Z 置信度 0.70
• Machine learning for long-haul optical systems
  crossref Shaoliang Zhang, Christian Häger 2022-03-18T10:02:05Z 置信度 0.70
• Machine learning for vibrational spectroscopy
  crossref Sergei Manzhos, Manabu Ihara, Tucker Carrington 2022-09-23T21:53:22Z 置信度 0.70
• Recent Advances in Machine Learning Strategies and Its Applications
  Today, machine learning is a widely used technique. An important artificial intelligence-led advancement in the field of digitalization solutions is machine learning, which was primarily a subcategory of artificial intelligence and attracted substantial attent…
  crossref S. Saranyadevi, Lekshmi Gangadhar 2025-01-28T19:00:48Z 置信度 0.70