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• 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 0.77 Machine Learning (cs.LG)FOS: Computer and information sciencesFOS: Computer and information sciences
• Journal of Student-Scientists' Research, Vol. 6 (2024)
  Abstracts submitted by the Aspiring Scientists Summer Internship Program cohort of 2024. Each describes an 8-week project conducted under faculty mentorship at George Mason University that was publically presented at our in-person or remote research symposiums…
  datacite Journal Of Student-Scientists' Research 2024 置信度 0.69 social and behavioral sciencespsychologymulti-agent systemscomputational neurosciencecognitive psychology
• Advancing Vascular Surgery: The Role Of Artificial Intelligence And Machine Learning In Managing Carotid Stenosis
  Introduction: Cardiovascular diseases affect 17.7 million people annually, worldwide. Carotid degenerative disease, commonly described as atherosclerotic plaque accumulation, significantly contributes to this, posing a risk for cerebrovascular events and ische…
  datacite Pias, Ana Daniela, Pereira-Macedo, Juliana, Marreiros, Ana, António, Nuno 等 2024 置信度 0.77 medicineartificial intelligencecomputer sciencehealth caredata science
• Machine learning applications in studying mental health among immigrants and racial and ethnic minorities: an exploratory scoping review
  Abstract Background The use of machine learning (ML) in mental health (MH) research is increasing, especially as new, more complex data types become available to analyze. By examining the published literature, this review aims to explore the current applicatio…
  datacite Park, Khushbu Khatri, Saleem, Mohammad, Al-Garadi, Mohammed Ali, Ahmed, Abdulaziz 2024 置信度 0.77 BiotechnologyBiological Sciences not elsewhere classifiedScience Policy
• Machine learning applications in studying mental health among immigrants and racial and ethnic minorities: an exploratory scoping review
  Abstract Background The use of machine learning (ML) in mental health (MH) research is increasing, especially as new, more complex data types become available to analyze. By examining the published literature, this review aims to explore the current applicatio…
  datacite Park, Khushbu Khatri, Saleem, Mohammad, Al-Garadi, Mohammed Ali, Ahmed, Abdulaziz 2024 置信度 0.77 BiotechnologyBiological Sciences not elsewhere classifiedScience Policy
• Single-cell transcriptomes identify patient-tailored therapies for selective co-inhibition of cancer clones
  Intratumoral cellular heterogeneity necessitates multi-targeting therapies for improved clinical benefits in advanced malignancies. However, systematic identification of patient-specific treatments that selectively co-inhibit cancerous cell populations poses a…
  datacite Ianevski, Aleksandr, Nader, Kristen 2024 置信度 0.77 medicinebiologypharmacologycancergenetics
• Single-cell transcriptomes identify patient-tailored therapies for selective co-inhibition of cancer clones
  Intratumoral cellular heterogeneity necessitates multi-targeting therapies for improved clinical benefits in advanced malignancies. However, systematic identification of patient-specific treatments that selectively co-inhibit cancerous cell populations poses a…
  datacite Ianevski, Aleksandr, Nader, Kristen 2024 置信度 0.77 medicinebiologypharmacologycancergenetics
• Collaborative learning of common latent representations in routinely collected multivariate ICU physiological signals
  In Intensive Care Units (ICU), the abundance of multivariate time series presents an opportunity for machine learning (ML) to enhance patient phenotyping. In contrast to previous research focused on electronic health records (EHR), here we propose an ML approa…
  datacite Haule, Hollan, Piper, Ian, Jones, Patricia, Lo, Tsz-Yan Milly 等 2024 置信度 0.77 Machine Learning (cs.LG)FOS: Computer and information sciencesFOS: Computer and information sciences
• The Impact of Technology and Digital Health on Cardiology: A Review of the Present to Reach the Future
  The integration of digital health technologies is revolutionizing the field of cardiology, particularly in the diagnosis, treatment, and management of cardiovascular diseases (CVDs). The rapid advancements in wearable devices, artificial intelligence (AI), and…
  datacite Couto Da Rocha, Sofia, Ramos, Alberto 2024 置信度 0.77 medicinecomputer sciencehealth caredata scienceartificial intelligence
• <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…
  datacite ortiz, Juan david 2024 置信度 0.76 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…
  datacite ortiz, Juan david 2024 置信度 0.76 Clinical chemistry (incl. diagnostics)
• Predicting Deterioration in Mild Cognitive Impairment with Survival Transformers, Extreme Gradient Boosting and Cox Proportional Hazard Modelling
  The paper proposes a novel approach of survival transformers and extreme gradient boosting models in predicting cognitive deterioration in individuals with mild cognitive impairment (MCI) using metabolomics data in the ADNI cohort. By leveraging advanced machi…
  datacite Musto, Henry, Stamate, Daniel, Logofatu, Doina, Stahl, Daniel 2024 置信度 0.77 Machine Learning (cs.LG)Artificial Intelligence (cs.AI)Neural and Evolutionary Computing (cs.NE)FOS: Computer and information sciencesFOS: Computer and information sciences
• Multi-Model Ensemble Approach for Accurate Bi-Atrial Segmentation in LGE-MRI of Atrial Fibrillation Patients
  Atrial fibrillation (AF) is the most prevalent form of cardiac arrhythmia and is associated with increased morbidity and mortality. The effectiveness of current clinical interventions for AF is often limited by an incomplete understanding of the atrial anatomi…
  datacite Beveridge, Lucas, Zhang, Le 2024 置信度 0.79 Image and Video Processing (eess.IV)Computer Vision and Pattern Recognition (cs.CV)FOS: Electrical engineering, electronic engineering, information engineeringFOS: Electrical engineering, electronic engineering, information engineeringFOS: Computer and information sciences
• Train-On-Request: An On-Device Continual Learning Workflow for Adaptive Real-World Brain Machine Interfaces
  Brain-machine interfaces (BMIs) are expanding beyond clinical settings thanks to advances in hardware and algorithms. However, they still face challenges in user-friendliness and signal variability. Classification models need periodic adaptation for real-life …
  datacite Mei, Lan, Cioflan, Cristian, Ingolfsson, Thorir Mar, Kartsch, Victor 等 2024 置信度 0.77 Signal Processing (eess.SP)Systems and Control (eess.SY)FOS: Electrical engineering, electronic engineering, information engineeringFOS: Electrical engineering, electronic engineering, information engineering
• Real-Time Machine Learning Strategies for a New Kind of Neuroscience Experiments
  Function and dysfunctions of neural systems are tied to the temporal evolution of neural states. The current limitations in showing their causal role stem largely from the absence of tools capable of probing the brain's internal state in real-time. This gap re…
  datacite Vermani, Ayesha, Dowling, Matthew, Jeon, Hyungju, Jordan, Ian 等 2024 置信度 0.77 Neurons and Cognition (q-bio.NC)FOS: Biological sciencesFOS: Biological sciences
• When Raw Data Prevails: Are Large Language Model Embeddings Effective in Numerical Data Representation for Medical Machine Learning Applications?
  The introduction of Large Language Models (LLMs) has advanced data representation and analysis, bringing significant progress in their use for medical questions and answering. Despite these advancements, integrating tabular data, especially numerical data pivo…
  datacite Gao, Yanjun, Myers, Skatje, Chen, Shan, Dligach, Dmitriy 等 2024 置信度 0.77 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
  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 0.76 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 0.76 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 0.72
• 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 0.72
• 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 0.68
• 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 0.68
• Self-supervised Speech Models for Word-Level Stuttered Speech Detection
  Clinical diagnosis of stuttering requires an assessment by a licensed speech-language pathologist. However, this process is time-consuming and requires clinicians with training and experience in stuttering and fluency disorders. Unfortunately, only a small per…
  datacite Shih, Yi-Jen, Gkalitsiou, Zoi, Dimakis, Alexandros G., Harwath, David 2024 置信度 0.79 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
  Decision-making is increasingly supported by machine recommendations. In healthcare, for example, a clinical decision support system is used by the physician to find a treatment option for a patient. In doing so, people can rely too much on these systems, whic…
  datacite Fischer, Simon WS 2024 置信度 0.77 Human-Computer Interaction (cs.HC)FOS: Computer and information sciencesFOS: Computer and information sciences
• 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…
  datacite Yang, Qihan, Gloumakov, Yuri, Spiers, Adam J. 2024 置信度 0.77 Robotics (cs.RO)Machine Learning (cs.LG)FOS: Computer and information sciencesFOS: Computer and information sciences
• Understanding eGFR Trajectories and Kidney Function Decline via Large Multimodal Models
  The estimated Glomerular Filtration Rate (eGFR) is an essential indicator of kidney function in clinical practice. Although traditional equations and Machine Learning (ML) models using clinical and laboratory data can estimate eGFR, accurately predicting futur…
  datacite Li, Chih-Yuan, Wu, Jun-Ting, Hsu, Chan, Lin, Ming-Yen 等 2024 置信度 0.77 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 0.79 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 0.77 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
  breast cancer ranks first in female malignant tumors. Early detection and diagnosis is the key to treatment. This paper uses the open-source load_break_cancer breast cancer data set, mainly uses random forest, support vector machine, logical regression, Gauss …
  crossref Meirui Song, Shixiao Wu, Rujuan Huang 2024-09-20T16:25:21Z 置信度 0.82 convolutional neural networkstat.mlartificial neural networkcs.lgartificial intelligence
• A Survey on Skin Lesion Detection and Classification using Machine Learning
  The research explores how dermatologists use machine learning to quickly and accurately identify and classify skin injury. Conventional diagnosis techniques depend on visual examination, but are subjective and have different interpretations. The ability to ana…
  crossref Rashmi Yadav, Aruna Bhat 2024-05-21T13:20:38Z 置信度 0.82 computer scienceartificial intelligencedata sciencedeep learninghealth care
• Integrated multi-omics analysis and machine learning developed diagnostic markers and prognostic model based on Efferocytosis-associated signatures for septic cardiomyopathy
  Septic cardiomyopathy (SCM) is characterized by an abnormal inflammatory response and increased mortality. The role of efferocytosis in SCM is not well understood. We used integrated multi-omics analysis to explore the clinical and genetic roles of efferocytos…
  crossref Xuelian Li, Shijiu Jiang, Boyuan Wang, Shaolin He 等 2024-06-27T14:50:30Z 置信度 0.82 medicinebiologycancergeneticsinternal medicine
• 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…
  crossref A. Lakshmi Bhargav, C. Ashokkumar 2025-01-17T18:33:03Z 置信度 0.82 medicineconvolutional neural networkcancercs.lgcomputer science
• Early Screening of Breast Cancer Using Machine Learning Algorithms: A Comparative Study
  Breast cancer is one of the most typical types of cancer in women. It is the second greatest cause of death for women worldwide. Early detection and treatment can raise the likelihood of a full recovery and decrease the risk of cancer spreading. Therefore, the…
  crossref Md Aminul Haque, Moname Majumder, Syed Mohammed Shamsul Islam 2025-02-17T18:27:08Z 置信度 0.82 artificial intelligencemedicinecomputer sciencecs.lgconvolutional neural network
• CoRe optimizer: an all-in-one solution for machine learning
  Abstract The optimization algorithm and its hyperparameters can significantly affect the training speed and resulting model accuracy in machine learning (ML) applications. The wish list for an ideal optimizer includes fast and smooth convergence to low error, …
  crossref Marco Eckhoff, Markus Reiher 2024-01-17T22:22:06Z 置信度 0.82 computer and information sciencescs.lgartificial intelligencecomputer scienceelectrical engineering, electronic engineering, information engineering
• Bridging efficacy and efficiency: Innovations in Shapley value estimation for model-agnostic data valuation in machine learning
  The escalating advancement of generative AI models amplifies the imperative for adept data valuation techniques. Amidst a myriad of methodologies, various Shapley value estimation techniques, such as Data Shapley, have garnered attention for their proficient d…
  crossref Yilu Yang 2024-04-01T14:12:58Z 置信度 0.82 computer sciencecs.lgartificial intelligencecs.aicomputer and information sciences
• Symbolic regression as a feature engineering method for machine and deep learning regression tasks
  Abstract In the realm of machine and deep learning (DL) regression tasks, the role of effective feature engineering (FE) is pivotal in enhancing model performance. Traditional approaches of FE often rely on domain expertise to manually design features for mach…
  crossref Assaf Shmuel, Oren Glickman, Teddy Lazebnik 2024-05-28T18:44:40Z 置信度 0.82 artificial intelligencecs.lgcomputer sciencecomputer and information sciencesmachine learning
• 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 …
  crossref Arthur R. C. McCray, Alec Bender, Amanda Petford-Long, Charudatta Phatak 2024-06-04T14:12:33Z 置信度 0.82 physicscs.lgconvolutional neural networkcomputer sciencecomputer and information sciences
• Chapter 14: Dynamic Programming and Reinforcement Learning
  Dynamic programming is one of the techniques used to solve the optimal control problem. Optimal control has been used in many different areas, like rocket control, chemical process control, and optimal economic growth. We will see in Chapter 19 the application…
  crossref 2024-03-26T11:03:09Z 置信度 0.76 math.oceess.sycontrolcontrol theorysystems and control
• Rethinking Machine Learning and Deep Learning
  crossref Makarand R. Velankar, Parikshit N. Mahalle, Gitanjali R. Shinde 2024-03-16T06:01:43Z 置信度 0.66
• 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…
  crossref 2024-12-12T05:27:18Z 置信度 0.82 computer sciencedata sciencebig datacloud computingfield
• Neural Networks and Deep Learning Architectures: From Basics to Advanced Implementations
  Neural network topologies and deep learning techniques have advanced so quickly that have drastically changed a number of fields, including computer vision and natural language processing. This book chapter explores the complex world of deep learning architect…
  crossref J Latha 2025-06-04T07:10:26Z 置信度 0.82 computer scienceartificial intelligencecs.lgcomputer and information sciencesdeep learning
• Construction of English Translation Practice Teaching Mode Based on Deep Learning Model
  Translation practice teaching occupies an important position in English teaching, but there are still many problems in the construction of the current English translation practice teaching mode. Guided by deep learning models and artificial intelligence, this …
  crossref 2024-04-14T03:12:10Z 置信度 0.82 mathematics educationpsychologymedical educationperceptioncs.hc
• Clustering
  crossref Hang Li 2023-12-06T00:02:11Z 置信度 0.57
• 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 …
  crossref 2024-06-03T07:42:56Z 置信度 0.82 computer sciencecs.lgartificial intelligencedata scienceq-bio.qm
• Boosting
  crossref Hang Li 2023-12-06T00:02:11Z 置信度 0.57
• Machine Learning Applications in Electric Vehicles: A Comprehensive Overview
  Electric vehicles (EVs) have emerged as a key solution to the environmental and energy challenges of modern transportation. As the industry evolves, machine learning (ML) technologies are playing an increasingly important role in optimizing EV performance, ene…
  crossref Suman Shrestha 2024-09-13T16:33:28Z 置信度 0.82 batteryengineeringbusinessenvironmental economicsenergy storage
• 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 0.82 computer sciencesystematic reviewhealth caretransparencytransformative learning
• 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 …
  crossref A. Thilaka, E. Sundaravalli 2024-05-21T17:20:38Z 置信度 0.82 cs.lgstat.mlartificial neural networkconvolutional neural networkmachine learning
• SST 2024 Machine Learning Breaker Page
  crossref 2024-11-20T18:57:29Z 置信度 0.66
• Proceedings
  crossref 2024-07-23T17:37:15Z 置信度 0.59
• Machine learning classification of new asteroid families members
  Asteroid families are groups of asteroids that are the product of collisions or of the rotational fission of a parent object. &amp;#160;These groups are mainly identified in proper elements or frequencies domains. &amp;#160; Because of robotic telescope survey…
  crossref Valerio Carruba 2020-10-08T09:23:31Z 置信度 0.79 biologyasteroidmeteoritechondriteastro-ph.ep
• Machine Learning
  crossref 2025-10-21T20:19:12Z 置信度 0.66
• Causal Economic Machine Learning (CEML)
  This paper proposes causal economic machine learning (CEML) as a research agenda that utilizes causal machine learning (CML) built on causal economics (CE) decision theory. Causal economics is better suited for use in machine learning optimization than expecte…
  crossref Andrew Horton 2024-08-20T01:25:23Z 置信度 0.82 computer sciencecs.lgartificial intelligencecomputer and information sciencesmachine learning
• New Paradigm in Financial Technology Using Machine Learning Techniques and Their Applications
  crossref Deepti Patnaik, Srikanta Patnaik 2024-08-27T02:02:03Z 置信度 0.66
• Proceedings of the 2024 2nd International Conference on Communication Networks and Machine Learning
  crossref 2025-02-19T07:08:06Z 置信度 0.66
• Advancements in Deep Learning
  Profound contemplating is essentially utilizing various layers of neurons to consistently remove better-degree highlights from the realities that we feed to the neural local area. Profound getting to realize models are absolutely one of the styles of the artif…
  crossref 2024-07-31T12:48:24Z 置信度 0.82 artificial intelligenceartificial neural networkcs.necognitive sciencecs.lg
• Applied Machine Learning for Predicting Crop Performance: A Supervised Learning Perspective
  Agriculture is fraught with uncertainty due to climate change, rainfall, soil types, and many other factors. Crop prediction in agriculture is a major dilemma and there are huge data sets where farmers struggle to predict the right seed. In this situation of p…
  crossref 2024-08-14T03:16:35Z 置信度 0.82 agricultureclimate changeenvironmental scienceartificial neural networkgreenhouse gas
• Determinants of Bitcoin Price: A Machine Learning Approach
  crossref Levent Kutlu 2024-04-30T15:53:20Z 置信度 0.66
• Perceptron
  crossref Hang Li 2023-12-06T00:02:11Z 置信度 0.57
• 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 …
  crossref Hongjin Wang, Chenxing Luo, Renata Wentzcovitch 2024-09-26T15:36:13Z 置信度 0.82 physicscond-mat.mtrl-scics.lgphysics.comp-phphysics.chem-ph
• 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…
  crossref Elham Shammar 2024-01-26T15:28:16Z 置信度 0.82 computer sciencemachine learningcomputer securitytransparencydata science
• Decision letter for "Quantum machine learning for image classification"
  crossref 2024-02-21T16:15:33Z 置信度 0.66
• 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 0.82 environmental sciencecs.lgartificial intelligencephysical sciencesremote sensing
• Proceedings of the 2024 7th International Conference on Signal Processing and Machine Learning
  crossref 2024-10-11T16:29:37Z 置信度 0.66
• 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…
  crossref Caleb Combs, Edgar Avalos Gauna, C. Fred Higgs 2025-03-04T18:39:11Z 置信度 0.82 cs.lgcomputer sciencestat.mlmachine learningartificial intelligence
• 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 0.82 computer sciencecs.lgartificial intelligencemachine learningpsychology
• 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.
  crossref Vazgen Melikyan 2023-12-30T10:02:41Z 置信度 0.72
• Organizing Committees
  crossref 2025-04-29T17:29:35Z 置信度 0.59
• Carbon Price Forecasting with Optimized Machine Learning Methods
  crossref Ozan Nadirgil 2024-07-16T10:22:21Z 置信度 0.66
• 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…
  crossref Shuai Liu, Hailiang Peng, Xiaolu Deng 2024-08-03T06:41:34Z 置信度 0.82 cs.lgartificial neural networkstat.mlcomputer scienceconvolutional neural network
• Reviewers: FMLDS 2024
  crossref 2025-02-17T18:27:08Z 置信度 0.59
• Review for "Machine learning interatomic potentials for amorphous zeolitic imidazolate frameworks"
  crossref 2024-09-27T00:02:30Z 置信度 0.66
• 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 0.82 biologycs.lgconvolutional neural networkenvironmental scienceclimate change
• 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
  crossref Gerald Friedland 2023-12-01T06:04:04Z 置信度 0.72
• 2024 IEEE 3rd Workshop on Machine Learning on Edge in Sensor Systems (SenSys-ML)
  crossref 2024-06-24T17:22:44Z 置信度 0.66
• ICBDML 2024 TOC
  crossref 2024-07-02T18:12:18Z 置信度 0.59
• Machine learning-assisted Fourier transform infrared and Raman spectroscopic sensing in agricultural and food systems
  crossref Tianjian Tong, Binbin Zhu, Chenxu Yu 2024-07-19T06:47:29Z 置信度 0.66
• Decision letter for "Quantum machine learning for image classification"
  crossref 2024-02-21T16:15:33Z 置信度 0.66
• 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 0.82 medicinebiological sciences not elsewhere classifiedinternal medicinepopulationmedline
• 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.…
  crossref John Tian, Yourui Shao 2025-02-17T18:27:08Z 置信度 0.82 artificial intelligencecomputer sciencecs.lgcs.aicomputer and information sciences
• MLCAD 2024 Cover Page
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