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• Comparative evaluation of deep learning models for three-class frailty assessment using gait metrics.
  Frailty assessment in older adults typically relies on subjective clinical tools that are time-consuming and require trained personnel, limiting their use in routine or large-scale screening. Wearable sensor-based gait analysis offers a promising objective alt…
  pubmed Hughes CML, Zhang Y 2026 置信度 0.96 interpretabilityconvolutional neural networkworkflowmedlinebiological sciences not elsewhere classified
• Artificial Intelligence Empowers Physical Therapy for Older Adults: A Perspective.
  Population aging has increased the demand for rehabilitation services due to multimorbidity and age-related functional decline. Physical therapy plays a central role in maintaining mobility and independence in older adults; however, increasing clinical complex…
  pubmed Huang H, Zhang C, Hao J 2026 Jul 置信度 0.96 health caremedicinemedical physicsmedlinetransformative learning
• Hyperspectral imaging in oral oncology: a scoping review.
  Oral cancer accounts for 177,000 deaths annually. Despite advances in surgical techniques and adjuvant therapies, the five-year survival rate for oral malignancies has shown limited improvement. Hyperspectral imaging (HSI) is a new non-invasive optical modalit…
  pubmed Kankawale S, Jamkhande A, Oka G 2026 置信度 0.96 medical physicsmedicinemedlinemedicine and health sciencesintensive care medicine
• Scanner-agnostic artificial intelligence approach for fast bone scintigraphy.
  Current bone scintigraphy protocols often demand full-count, 10-15 min scans to preserve image quality, and existing deep-learning (DL) denoisers typically need to be retrained or retuned for each camera manufacturer. We introduce a scanner-agnostic adapt…
  pubmed Menezes VO, Queiroz CC, Oliveira AAS, Santos Filho AJD 等 2026 Aug 置信度 0.96 cs.cvcomputer vision and pattern recognitioneess.ivcryptography and securityoptics
• The Relationship between Biological Aging and Cognitive Function: A Machine Learning Model.
  The relationship between cognitive impairment and biological age (BA) is unclear. This study aimed to investigate the association between BA and cognitive impairment.
  pubmed Ren C, Li Z, Cai J, Li J 等 2026 Jul 置信度 0.93 cognitionpsychologycognitive psychologyinternal medicinesocial and behavioral sciences
• Prediction of Clinically Significant Improvement after Lumbar Fusion Surgery Based on Machine Learning.
  Lumbar fusion surgeries have increased substantially, making patient satisfaction an important indicator of surgical outcomes and quality of care. Conventional statistical approaches have limitations in predicting clinically significant improvement (CSI). This…
  pubmed Cho H, Lee D, Kim S, Noh SH 2026 置信度 0.96 medicineinternal medicinemedlinemedical physicsintensive care medicine
• A projection-domain deep learning approach for respiratory motion correction of myocardial perfusion imaging using a multi-pinhole solid-state SPECT.
  Myocardial perfusion imagining (MPI) is a nuclear medicine technique used in the assessment of coronary artery disease. Differences in the perfusion of the myocardium at rest and stress and regions of perfusion defects can be indicators of various cardiac dise…
  pubmed Malenfant DJ, Ruddy TD, Wells RG 2026 Aug 置信度 0.96 cs.cvelectrical engineering, electronic engineering, information engineeringdiseasenetworking and internet architecturemedicine
• Accurate automated 3D lumbar spine reconstruction from biplanar X-rays using multi-task deep learning and anatomy-aware optimization.
  Accurate 3D assessment of the weight-bearing lumbar spine is crucial for diagnosing various spinal pathologies. However, existing biplanar X-ray reconstruction methods struggle with complex pathologies and low-contrast structures.
  pubmed Yu W, Zhu Z, Wang C, Bao Y 等 2026 Aug 置信度 0.89 medical physicseess.ivcs.cvcontrolneuromorphic computing
• Quantitative CRFF-OCT Imaging Features for Characterization of Disease Activity in Non-Segmental Vitiligo: A Machine Learning-Assisted Study.
  Vitiligo is an autoimmune pigmentary disorder characterized by progressive melanocyte loss and unpredictable activity. Objective of disease activity remains challenging, particularly in lesions with subtle clinical changes Cellular-resolution full-field optica…
  pubmed Ng CY, Chen IL, Chen YT, Tsai FL 等 2026 Jul 置信度 0.96 medicineneurosciencebiological sciences not elsewhere classifiedbrain-computer interfacescience policy
• A modality-agnostic coronary artery habitat model for cardiac sparing in radiotherapy.
  Emerging evidence suggests that the risk of cardiotoxicity increases with increased radiation dose to coronary arteries (CAs). However, robust tools to evaluate this increased burden for cancer patients are not available due to current limitations in imaging f…
  pubmed Ruff C, Summerfield N, Dong M, Nagpal P 等 2026 Aug 置信度 0.83 medicineinternal medicinemedical physicscancerdisease
• Multiscale frequency attention transformer for resolution enhancement in magnetic particle imaging.
  Magnetic particle imaging (MPI) is an emerging functional imaging modality that enables high-resolution (HR) visualization of superparamagnetic iron oxide nanoparticles (SPIONs). It offers significant advantages, including high penetration capability, absence …
  pubmed Jiang W, Xu J, Yang X, He N 等 2026 Aug 置信度 0.96 opticsquantum dotneuroimagingmaterials sciencechemical engineering
• Targeting progressive multiple sclerosis: Toward mechanism-informed precision medicine.
  Multiple sclerosis has undergone a therapeutic revolution over the past three decades. Randomized clinical trials and real-world data demonstrate that modern disease-modifying therapies substantially reduce relapse rates and acute inflammatory activity detecte…
  pubmed Piehl F, Castelo-Branco G, Jagodic M, Olsson T 2026 Sep 置信度 0.96 medicineartificial intelligencediseasebiologypharmacology
• A bladder cancer-associated gene signature for exploratory qPCR-based survival stratification in NAC-Treated muscle-invasive bladder cancer.
  Muscle-invasive bladder cancer (MIBC) is an aggressive and heterogeneous malignancy with limited biomarkers to guide patient stratification and response to neoadjuvant chemotherapy (NAC). We sought to define the biological basis and clinical utility of a bladd…
  pubmed Chen X, Sakatani T, Tanaka S, Contreras-Sanz A 等 2026 Jul 21 置信度 0.93 medicinediseasemedical physicsintensive care medicineinternal medicine
• Machine learning-based clinical models for prediction of urinary incontinence after robot-assisted laparoscopic radical prostatectomy.
  To investigate risk factors for urinary incontinence (UI) after robot-assisted laparoscopic radical prostatectomy (RARP) using interpretable machine learning methods, establish and validate a predictive model.
  pubmed Wang X, Yuan Y, Zhou P, Gu B 等 2026 置信度 0.93 interpretabilitystat.mlcomputer and information sciencesscaledistributed computing
• Non-invasive diagnostic evaluation of urinary exosomal let-7c cluster expression in bladder cancer using machine learning approaches.
  Bladder cancer (BCa) diagnosis typically relies on invasive cystoscopy, which is effective but costly and uncomfortable. Urinary microRNAs (miRNAs), especially exosomal ones, are promising non-invasive biomarkers due to their stability in biological fluids and…
  pubmed Kural S, Kumar L, Pathak AK, Singh S 等 2026 Jul 21 置信度 0.96 medicinebiochemistrynanotechnologydiseaseneuroscience
• Interpretable Machine Learning Model for Predicting Sepsis and Septic Shock Among Patients with Documented Fever at Emergency Department Triage Using Patients' Historical Data.
  This study aimed to develop an interpretable machine learning-based scoring system for predicting sepsis and septic shock among febrile patients at emergency department (ED) triage using longitudinal data. This retrospective, single-center study included adult…
  pubmed Maeng SJ, Lee YR, Lee SU, Yu JY 等 2026 Jul 21 置信度 0.96 medicineinternal medicineintensive care medicinecs.lgcs.ai
• The use of artificial intelligence in advancing molecular biology in Africa: a narrative review.
  Artificial intelligence (AI) is rapidly becoming a core methodological pillar of molecular biology and precision medicine, and Africa is a uniquely consequential setting for this transition because the continent combines the world's greatest human genomic dive…
  pubmed Awuah D, Hounkpe A, Anane-Asamoah J, Dakubo WK 等 2026 Jul 22 置信度 0.96 biologyartificial intelligencecs.aicomputational biologydata science
• Multi-Axial Analysis of Clinical Reasoning in Large Language Models: Inter-Verifier Disagreement and Its Implications for Automated Evaluation.
  Evaluating clinical reasoning in large language models (LLMs) poses two open challenges: reference-oriented semantic metrics do not directly assess whether a model's stated diagnosis is supported by the evidence in its own justification, and the increasingly p…
  pubmed Byun H, Lee D, Jung M, Jang B 2026 Jul 22 置信度 0.96 artificial intelligencecs.aipsychologycomputer sciencemedicine
• Identification and validation of an explainable screening model of college students' mental health with therapeutic strategy implications.
  Mental health issues, especially depressive symptoms, among young adults represent a public health challenge. Conventional psychological assessment tools have limited sensitivity and specificity for identifying individuals at risk. This study aims to develop a…
  pubmed Liu K, Li Z, Zhao YY, Li X 等 2026 置信度 0.96 medicineartificial intelligencemental healthinternal medicinescience policy
• Development of a risk prediction model for rheumatoid arthritis-associated interstitial lung disease based on interpretable machine learning.
  This study constructed a predictive model for interstitial lung disease (ILD) in patients with rheumatoid arthritis (RA) and explored the value of interpretable machine learning.
  pubmed Li X, Yuan J, Li C, Luo M 等 2026 Sep 置信度 0.93 internal medicineintensive care medicinebiological sciences not elsewhere classifieddiseasemedicine
• Real-world deployment of remote sleep monitoring technologies reveals distinct patterns associated with cognitive decline.
  Examining sleep patterns in relation to chronological ageing and dementia can provide insights for risk screening. Integrating predictive models with remote sleep monitoring enables routine assessment of cognitive decline symptoms in high-risk groups, aiding e…
  pubmed Fletcher-Lloyd N, Gómez NC, Capstick A, Fogel A 等 2026 Jul 21 置信度 0.96 medicinepsychologyartificial intelligencescience policyinternal medicine
• Sex-specific predictors of lower-limb strength: an interpretable machine learning analysis of anthropometric and body composition measures.
  Muscular strength is a key indicator of physical function. However, its direct laboratory assessment often requires specialized, high-cost equipment and can impose significant physical fatigue or safety risks for certain populations, limiting its routine imple…
  pubmed Kang JH, Jeon YJ, So JH, Moon J 等 2026 Jul 21 置信度 0.96 medicinescience policybiological sciences not elsewhere classifiedbiological sciencessociology
• A multidimensional benchmarking framework for large language models in oncologic decision making.
  Large language models (LLMs) are increasingly explored as clinical decision support tools in oncology; however, reliance on isolated metrics has limited the development of multi-dimensional evaluation frameworks. This comparative observational study utilized f…
  pubmed Halici M, Salturk S, Sayin I, Ertan B 等 2026 Jul 21 置信度 0.96 medicineartificial intelligencecs.aicomputer sciencemedical physics
• Machine learning-based analysis of risk factors and construction of a predictive model for hyperuricemia in Chinese health examination population.
  Hyperuricemia (HUA) imposes a growing public health burden, calling for better risk stratification tools. In this cross-sectional study of 4906 Chinese adults undergoing routine health checks (overall HUA prevalence: 26.0%), we built machine learning-based pre…
  pubmed Tan C, He X, Li L, Li Y 等 2026 Jul 21 置信度 0.96 medicinebiological sciences not elsewhere classifiedcancerbiotechnologyintensive care medicine
• A multi-outcome prognostic score for therapeutic responses in multiple sclerosis.
  Multiple sclerosis (MS) is marked by heterogeneous disease activity, progression, and therapeutic response. Here, we developed a prognostic score based on machine learning using randomized clinical trials (RCTs) and observational datasets. The score's ability …
  pubmed Louet J, Paris J, Faddeenkov I, Payet M 等 2026 Jul 21 置信度 0.96 medicinecomputer sciencebrain-computer interfacecancerphysical medicine and rehabilitation
• Retraction notice to "Molecular structure of NRG-1 protein and its impact on adult hypertension and heart failure: A new clinical Indicator diagnosis based on advanced machine learning" [Int. J. Biol. Macromol. 304 (2025) 140955].
  pubmed Bai Q, Chen H, Liu H, Li X 等 2026 Sep 置信度 0.77
• Deep learning approaches for predicting response to neoadjuvant chemotherapy in muscle invasive bladder cancer: A systematic review.
  Neoadjuvant chemotherapy (NAC) followed by radical cystectomy is the standard of care for muscle-invasive bladder cancer (MIBC), yet treatment response is highly variable and current clinical predictors are inadequate. Deep learning (DL) offers a data-driven a…
  pubmed Nowroozi MR, Madani MH, Farzin A, Mazdak M 等 2026 Sep 置信度 0.96 medicinemedlineartificial intelligencemedical physicscomputer science
• Benchmarking large language models for de-identification of electronic health record notes.
  The rapid evolution of large language models (LLMs) and their growing application in clinical text processing have created an urgent need for reliable de-identification mechanisms. While LLMs show promise in identifying sensitive health information (SHI), thei…
  pubmed Panchal O, Chang NW, Zhao ZR, Nadar DR 等 2026 Jul 21 置信度 0.96 cs.clcomputer sciencecs.aidata sciencegenerative grammar
• Machine learning for COVID-19 mortality prediction: enhancing cart models with node-specific odds ratios.
  The objective of the study is to evaluate a classification and regression tree (CART) model combined with odds ratio (OR) to identify key predictors of COVID-19 mortality. Data from 1,432 patients hospitalized at Hospital General de México during the pand…
  pubmed Pérez-Pacheco A, Herrera-Suárez AE, Vélez-Mata J, Magdaleno-Fourlong LM 等 2026 置信度 0.93 internal medicinemedlinemedicineneuroimagingintensive care medicine
• cfDNA derived gene signatures as surrogate for microvascular invasion in HCC.
  Microvascular invasion (MVI) is a critical prognostic risk factor in hepatocellular carcinoma (HCC). This study evaluated the performance of 5-hydroxymethylcytosine (5hmC) modifications in circulating cell-free DNA (cfDNA) in preoperative assessment of MVI.
  pubmed Gong R, Wang L, Xue D, Cai J 等 2026 Jul 21 置信度 0.83 internal medicinecomputationnetworking and internet architecturepopulationmathematics education
• Real-World Evidence-Based Study on Treatment-Free Remission in Chronic Myeloid Leukemia.
  Treatment-free remission (TFR) has become a treatment goal for chronic myeloid leukemia (CML). This study aimed to define precise conditions for treatment discontinuation and to develop TFR prediction models in a Chinese population.
  pubmed Cheng F, Wang Y, Zhu Y, Yang Y 等 2026 Jul 21 置信度 0.83 intensive care medicinemicrobiologytraditional chinese medicineidentificationinternal medicine
• Agentic genomics: From pipeline automation to autonomous validation.
  Genomics has entered a phase in which AI agents can autonomously discover, configure, execute, and chain bioinformatics operations from natural-language instructions. We term this paradigm "agentic genomics": the delegation of multi-step genomic analyses to au…
  pubmed Corpas M, Guio H, Fatumo S 2026 Aug 12 置信度 0.96 cs.aimulti-agent systemsai governancecs.lgcs.se
• A wearable electrochemical aptamer platform based on microneedles for continuous real-time multiplexed hormone monitoring to advance hormone-related health management.
  Real-time, multiplexed monitoring of sex hormones is essential for managing reproductive health and endocrine disorders. Traditional invasive blood sampling lacks the temporal resolution required to capture the dynamic hormonal fluctuations necessary for perso…
  pubmed Zhou G, Ren G, Cheng Y, Guo L 等 2026 Nov 15 置信度 0.96 medicinecomputer sciencebiologymaterials scienceintensive care medicine
• How machine learning could be used in clinical practice during an epidemic
  crossref Charles Verdonk, Franck Verdonk, Gérard Dreyfus 2020-05-26T17:03:35Z 置信度 0.64
• Minimal Patient Clinical Variables to Accurately Predict Stress Echocardiography Outcome: Validation Study Using Machine Learning Techniques (Preprint)
  BACKGROUND Stress echocardiography is a well-established diagnostic tool for suspected coronary artery disease (CAD). Cardiovascular risk factors are used in the assessment of the probability of CAD. The link between the outcome of stress echocardiography and …
  crossref Mohamed Bennasar, Duncan Banks, Blaine A Price, Attila Kardos 2019-11-11T18:31:03Z 置信度 0.79 medicinebrain-computer interfaceartificial intelligenceinternal medicinecs.lg
• Application of machine learning approaches in predicting clinical outcomes in older adults – a systematic review and meta-analysis.
  Abstract Background Machine learning-based prediction models have the potential to have a considerable positive impact on geriatric care. Design: Systematic review and meta-analyses. Participants: Older adults (≥ 65 years) in any setting. Intervention: Machine…
  crossref Robert T Olender, Sandipan Roy, Prasad S Nishtala 2022-11-19T18:09:57Z 置信度 0.79 medicinemedlineartificial intelligencescience policysystematic review
• Probabilistic Expert Systems for Reasoning in Clinical Depressive Disorders
  Like other real-world problems, reasoning in clinical depression presents cognitive challenges for clinicians. This is due to the presence of co-occuring diseases, incomplete data, uncertain knowledge, and the vast amount of data to be analysed. Current approa…
  crossref Blessing Ojeme, Audrey Mbogho, Thomas Meyer 2017-02-07T20:39:53Z 置信度 0.74 computer sciencecs.lgcs.aics.cvelectrical engineering, electronic engineering, information engineering
• Machine learning prediction of side effects for drugs in clinical trials
  Early and accurate detection of side effects is critical for the clinical success of drugs under development. Here, we aim to predict unknown side effects for drugs with a small number of side effects identified in randomized controlled clinical trials. Our ma…
  crossref Diego Galeano, Alberto Paccanaro 2022-12-07T10:39:06Z 置信度 0.79 medicinecancerdiseasetraditional chinese medicinetraditional medicine
• How machine learning facilitates decision making in emergency departments: Modelling diagnostic test orders
  Objectives Since emergency departments (EDs) are responsible for providing initial care for patients who may need urgent medical care, they are highly sensitive to increased patient delays. A key factor that increases patient delays is ordering diagnostic test…
  crossref Görkem Sariyer, Mustafa Gökalp Ataman 2021-10-12T13:27:19Z 置信度 0.79 medicinecomputer sciencescience policyinternal medicinehealth care
• Training machine learning-based spirometry reference equations: a comparison with GAMLSS and GLI reference equations
  Introduction Interpretation of spirometry data depends on the availability of reference equations that reflect the physiological norms of the assessed population. Although GAMLSS models provide clinically acceptable models, they may lack simplicity and ease of…
  crossref Walid Al-Qerem, Anan Jarab, Judith Eberhardt 2025-10-03T17:34:34Z 置信度 0.82 medicineartificial intelligencepsychologybiological sciences not elsewhere classifiedmachine learning
• Machine learning–based construction of a clinical prediction model for hypercapnia during one-lung ventilation for lung surgery
  Abstract In this study, we developed a clinical prediction model for hypercapnia during one-lung ventilation for lung surgery by machine learning. We analyzed the cases and intraoperative blood gases of 348 patients who had undergone lung surgery at Jiangxi Ca…
  crossref Yiwei Fan, Ting Ye, Tingting Huang, Huaping Xiao 2022-09-13T16:00:33Z 置信度 0.79 medicineinternal medicinemedlineintensive care medicinemedical physics
• Predicting Clinical Trial Site Performance using Machine Learning
  Success of clinical trials depends extensively on the operational performance of the participating site, yet early detection of underperforming sites remains an ongoing challenge. In this work, the authors are presenting a machine learning-based framework for …
  crossref Sumanth Singh 2026-04-15T19:22:14Z 置信度 0.82 medicineartificial intelligencecomputer sciencemedical physicsmachine learning
• Machine learning techniques in biomedical data analysis: A scoping review of biostatistical perspectives
  Background Machine learning (ML) is increasingly applied in biomedical research to analyse complex datasets from imaging, omics, clinical records, and other sources. However, the extent to which biostatistical methods are integrated into ML applications remain…
  crossref A. Usha, Noel George, K. Janagi, Pradyuman Verma 2026-04-17T15:51:58Z 置信度 0.82 medicineartificial intelligencecomputer sciencemedlineinterpretability
• Machine learning for survival prediction after brain tumor stereotactic radiosurgery: A systematic review and meta-analysis
  Brain tumors remain a significant global health burden, contributing to substantial morbidity and mortality worldwide [1,2]. These neoplasms encompass a wide spectrum of conditions, including primary brain tumors, such as gliomas, and brain metastases [3,4]. G…
  crossref Anna Volodina, Aline Pinto Veiga, Imran Noorani 2026-05-26T10:14:45Z 置信度 0.82 medicineintensive care medicinediseaseneuroscienceinternal medicine
• Comment on “Prediction of venous thromboembolism after spontaneous intracerebral hemorrhage based on machine learning”
  crossref Sadhana U. Adhyapak, Abhishek Kumar Upadhyay, S.R.V. Prasad Reddy 2026-05-18T06:02:59Z 置信度 0.66
• Relevance of Machine Learning to Cardiovascular Imaging
  Artificial intelligence (AI) broadly concerns analytical algorithms that iteratively learn from big datasets, allowing computers to find concealed insights. These encompass a range of operations comprising several terms, including machine learning(ML), cogniti…
  crossref Sumesh Sasidharan, M. Yousuf Salmasi, Selene Pirola, Omar A. Jarral 2020-08-06T09:19:37Z 置信度 0.79 computer scienceartificial intelligencedata sciencemachine learninghealth care
• Classification of schizophrenia spectrum disorder using machine learning and functional connectivity: reconsidering the clinical application
  Abstract An accurate identification of schizophrenia spectrum disorder (SSD) at early stage could potentially allow for treating SSD with appropriate intervention to potentially prevent future deterioration. Despite mounting studies found neuroimaging combined…
  crossref Chao Li, Fei Wang, Xiaowei Jiang, Ji Chen 等 2020-06-03T14:51:57Z 置信度 0.79 medicinecs.lgartificial intelligencepsychologycs.ai
• Machine learning predictive model based on the corneal biomechanics of clinical data
  Objective To develop and validate a machine learning model for predicting postoperative corneal ectasia risk after refractive surgery by integrating multidimensional preoperative and postoperative biomechanical parameters. Methods A retrospective cohort of 200…
  crossref Tianyu Shi 2025-10-18T16:23:43Z 置信度 0.82 medicineinternal medicinebiological sciences not elsewhere classifiedcomputer sciencecancer
• Machine Learning in oncology: A clinical appraisal
  Machine learning (ML) is a branch of artificial intelligence centered on algorithms which do not need explicit prior programming to function but automatically learn from available data, creating decision models to complete tasks. ML-based tools have numerous p…
  crossref Renato Cuocolo, Martina Caruso, Teresa Perillo, Lorenzo Ugga 等 2020-04-03T20:35:52Z 置信度 0.79 computer scienceartificial intelligencedata sciencehealth caremedicine
• Accurate Heart Disease Prediction Using Machine Learning Techniques on Clinical Data
  Heart disease is still one of the main causes of mortality in the world, and its early diagnosis represents an important part of timely treatment and prevention.The purpose of this work is to create a stable and accurate Machine Learning (ML) model for predict…
  crossref Sunanda Budihal, Sheetalrani R. Kawale 2025-12-18T19:14:01Z 置信度 0.82 medicineartificial intelligencecomputer scienceinternal medicinemachine learning
• The faces of sleep apnea in the age of machine learning
  crossref Ofer Jacobowitz, Stuart MacKay 2020-03-17T15:44:36Z 置信度 0.64
• Comment on “Interpretable machine learning model for predicting refeeding syndrome after colorectal cancer surgery”
  crossref P S L Narasimharao Davuluri, Avinash Reddy Segireddy, Goutham Kumar Sheelam 2026-05-18T23:35:00Z 置信度 0.66
• The Use of Artificial Intelligence and Machine Learning in Clinical Research and Health Care
  Conference Education Session Report Speaker J. Kelly Byram, MS, MBA, ELS, Founder and CEO, Duke City Consulting, LLC, Albuquerque, NM
  crossref Noelle Ochotny 2023-03-02T14:46:48Z 置信度 0.72
• Figure 10: Differences between (A) traditional machine learning and (B) transfer learning.
  crossref 2025-01-14T03:30:26Z 置信度 0.66
• Machine Learning and Deep Learning in Quantitative Finance
  <span>This paper systematically reviews the technological evolution and practical applications of machine learning and deep learning in key areas such as stock price prediction, market timing, factor investing, and portfolio optimization. By leveraging a…
  crossref Fanqun Mo 2026-07-29T13:20:29Z 置信度 0.82 computer scienceartificial intelligencemachine learningcs.lgdata science
• The Price Prediction of Sneakers Based on Machine Learning
  Abstract-Sneaker culture is a self-organizing culture spontaneously formed by teenagers. In the Internet and digital age, sports shoes are endowed with appreciation and financial attributes through manual speculation, which has triggered a wave of sports shoes…
  crossref WeiJia Yan 2022-04-29T20:07:24Z 置信度 0.79 cognitioncs.lgstat.mlartificial neural networkconvolutional neural network
• Machine Learning for Information Management: Some Promising Directions
  Management of personal information such as email messages, calendar entries, to-do items, and workstation documents is one of the most highly visible current uses of computer technology. I will present experimental evidence that machine learning techniques can…
  crossref Dr. William Cohen 2008-04-28T13:34:00Z 置信度 0.75 computer scienceartificial intelligencecs.lgstat.mlbrain-computer interface
• Architecture of a Machine Learning IDS
  crossref Emmanuel Tsukerman 2020-10-07T16:04:31Z 置信度 0.64
• Machine Learning in Chinese Courts
  Abstract This chapter focuses on core machine learning (ML) technologies such as Optical Character Recognition (OCR) and Automatic Speech Recognition (ASR) technology in the context of how Chinese courts have sought to improve court efficiency and reduce the p…
  crossref Nyu Wang, Michael Yuan Tian 2024-07-18T15:54:17Z 置信度 0.82 computer scienceengineering ethicstransformative learningcontextbusiness
• Machine learning-based real-time detection of residual wall thickness in industrial pipelines
  Far-field eddy current detection technology is a special eddy current technology that utilizes electromagnetic effect to detect the pipe through the wall. This paper introduces the principle of the far-field eddy current detection technology, including the two…
  crossref 2024-07-14T08:57:24Z 置信度 0.82 risk analysisinterpretabilityai safetyconvolutional neural networkinstrumentation and methods for astrophysics
• Quality Control Method of Exploration and Development Data Based on Machine Learning
  Because of increased exploration depth and increasingly complex geological environment survey area, makes the actual acquired seismic exploration data contains a lot of noise, the noise composition is serious interference signal effectively, affect the signal …
  crossref 2023-02-06T01:45:11Z 置信度 0.79 convolutional neural networkwirelessinternet of thingsinstrumentation and methods for astrophysicsgeology
• Machine Learning Algorithms
  Human intelligence is deeply involved in creating efficient and faster systems that can work independently. Creation of such smart systems requires efficient training algorithms. Thus, the aim of this chapter is to introduce the readers with the concept of mac…
  crossref Namrata Dhanda, Stuti Shukla Datta, Mudrika Dhanda 2022-07-08T11:31:23Z 置信度 0.79 computer sciencecs.lgartificial intelligencereinforcement learningcs.ce
• Receiving information on machine learning-based clinical decision support systems in psychiatric services increases staff trust in these systems: A randomized survey experiment
  Abstract Background Clinical decision support systems based on machine learning (ML) models are emerging within psychiatry. To ensure their successful implementation, healthcare staff needs to trust these systems. Here, we investigated if providing staff with …
  crossref Erik Perfalk, Martin Bernstorff, Andreas Aalkjær Danielsen, Søren Dinesen Østergaard 2024-09-10T19:05:20Z 置信度 0.82 computer sciencepsychologymedicinehealth caremedical education
• Advancing Biomedical Engineering With Artificial Intelligence and Machine Learning: A Systematic Review
  The inclusion of artificial intelligence (AI) and machine learning (ML) in biomedical engineering opens new frontiers of innovation and better decision‐making and allows the art to cross new thresholds in healthcare technologies. This review focuses on the pri…
  crossref Abebe Belay Adege 2025-07-29T07:48:38Z 置信度 0.82 computer sciencedata sciencehealth caretransformative learningengineering ethics
• Support Vector Machine
  crossref Zhi-Hua Zhou 2021-08-20T19:23:05Z 置信度 0.64
• Machine Learning-Driven Adaptive Communication Systems and Beyond-6G Network Intelligence
  The transition toward beyond-6G communication networks introduces unprecedented challenges associated with ultra-low latency, massive connectivity, and highly dynamic service environments, demanding a paradigm shift from conventional static architectures to in…
  crossref R. Jegadeesan, Prerana Arun Wankhede 2026-05-13T04:03:28Z 置信度 0.82 computer sciencecomputer and information sciencesartificial intelligenceelectrical engineering, electronic engineering, information engineeringnetworking and internet architecture
• Research on Automated Risk Detection Methods in Machine Learning Integrating Privacy Computing
  As the digitalization process of enterprises accelerates, various application interfaces have become key hubs for system interconnection and data exchange.At the same time, they may also serve as entry points for attackers to obtain sensitive information.Witho…
  crossref 2025-11-21T09:43:36Z 置信度 0.82 computer scienceartificial intelligencecomputer and information sciencescomputer securitycs.lg
• Responsible Use of Machine Learning in Sports Science
  crossref Fabian Wunderlich 2025-07-21T23:08:52Z 置信度 0.66
• Machine Learning for Detecting Malware in PE Files
  The increasing number of sophisticated malware poses a significant cybersecurity threat. Portable executable (PE) files are a common vector for such malware. We review and evaluate machine learning-based PE malware detection techniques in this work. Using a la…
  crossref Collin Connors, Dilip Sarkar 2024-03-19T18:08:18Z 置信度 0.80 convolutional neural networkcs.lgmedlinedeep learningintensive care medicine
• Research on Vehicle Logistics Optimization Distribution Based on Machine Learning
  In order to solve the problems of low efficiency, unscientific management and large amount of manual work in the process of logistics distribution of enterprise products, a vehicle mounted logistics optimization distribution model is designed based on machine …
  crossref Ronghu Zhou 2023-03-07T18:42:09Z 置信度 0.79 math.ocdistributed computingsupply chaineess.syinformation theory
• Elizabeth Degefe Discusses Research Findings, Improving, and Resources for Future Research Using Machine Learning to Study Racism
  crossref 2023-03-24T08:31:51Z 置信度 0.64
• Optimization Basics: A Machine Learning View
  crossref Charu C. Aggarwal 2020-05-12T22:02:28Z 置信度 0.64
• Using Background Knowledge to Build Multistrategy Learners
  crossref Claude Sammut 2002-12-22T04:48:21Z 置信度 0.55
• Machine Learning Fundamentals
  Machine learning covers a large group of computational methods built upon past data and experience. This chapter serves as a gentle introduction to machine learning fundamentals. It covers key concepts of machine learning tasks, methods, and applications. The …
  crossref Yan Yan 2022-10-21T21:26:07Z 置信度 0.79 cs.lgartificial intelligencecomputer sciencestat.mlmachine learning
• Determining Student's Engagement in Synchronous Online Classes Using Deep Learning (Compute Vision) and Machine Learning
  In 2020 Scaled-YOLOv4 was introduced. It is one of the best object detection models outclassing its peers in MS COCO test-dev. In this study, the proponents used Scaled-YOLOv4 as their object detection model. The model will be used in the environment of Pasig …
  crossref John Paul Quilingking Tomas, Daniel Oliver Ancheta, Carl Andrei Aquino, Aerol Ortiz 2023-03-06T12:14:02Z 置信度 0.79 convolutional neural networkremote sensingcomputer vision and pattern recognitioncs.cvastro-ph
• Supplemental Information 7: Machine Learning Code.
  crossref 2026-02-10T08:19:16Z 置信度 0.66
• Understanding the core algorithms behind machine learning: Key learning algorithms explained
  Machine learning is a branch of artificial intelligence. It enables computers to automatically learn and improve from experience without being explicitly programmed [1]. Machine learning algorithms are usually classified into supervised, unsupervised, neural n…
  crossref Priyambada Swain 2025-08-16T18:24:01Z 置信度 0.82 cs.lgartificial intelligencecomputer sciencemachine learningstat.ml
• Randomly Fallible Teachers: Learning Monotone DNF with an Incomplete Membership Oracle
  crossref Dana Angluin, Donna K. Slonim 2003-04-04T16:55:36Z 置信度 0.58
• Learning Nonoverlapping Perceptron Networks from Examples and Membership Queries
  crossref Thomas R. Hancock, Mostefa Golea, Mario Marchand 2003-04-04T16:55:36Z 置信度 0.58
• Machine Learning in Molecular Dynamics Applications in Medicinal Chemistry
  Machine learning (ML) with molecular dynamics (MD) simulations represents a transformative approach in medicinal chemistry and computational biology, offering unprecedented insights into the dynamic behavior of molecular systems. The advent of ML has further r…
  crossref Sk Abdul Amin, Supratik Kar, Stefano Piotto 2026-07-22T08:41:26Z 置信度 0.82 computer sciencedrug discoverycomputational biologytransformative learningdata science
• Machine Learning for Mask Synthesis
  crossref Seongbo Shim, Suhyeong Choi, Youngsoo Shin 2019-03-15T12:32:24Z 置信度 0.64
• Research on Integration and Optimization Strategies of Cross-platform Machine Learning Services
  In diverse operating system environments, cross platform machine learning techniques are increasingly becoming the core means of enhancing data processing capabilities and model performance.This study aims to explore the integration and optimization path of cr…
  crossref 2026-01-12T09:54:59Z 置信度 0.82 computer scienceartificial intelligencemachine learningcloud computingdata science
• Transforming Pharma with Data Science, AI and Machine Learning
  This chapter provides an overview of transformative changes occurring in pharma engendered by big data and artificial intelligence (AI) and discusses the importance of data strategy in realizing full potential of these technology advances in the lifecycle of d…
  crossref Harry Yang 2022-08-12T20:20:36Z 置信度 0.79 health caredata sciencebig datatransformative learningcomputer science
• Recent Advances in Drug Design With Machine Learning
  Machine learning (ML) methods have been of special attention, since they can be utilized in numerous steps of the drug discovery process, for example, investigating biological activity of new candidates through construction of model, prediction of target struc…
  crossref Muhammad Faisal 2022-10-07T07:21:48Z 置信度 0.79 computer sciencedrug discoverydata sciencecs.lgcomputational biology
• Monetizing Finance Machine Learning
  In this chapter, I am going to put forward some innovative ideas that can be monetized using machine learning in the financial world. I will also show you some examples where a similar approach has been used and has succeeded. For some of them, there may not b…
  crossref Puneet Mathur 2018-12-12T14:05:50Z 置信度 0.76 stat.mlconvolutional neural networkcs.itbig dataphysics.pop-ph
• Machine Learning in Cardiovascular Disorders
  crossref Shyamasree Ghosh, Rathi Dasgupta 2022-05-04T17:03:22Z 置信度 0.64
• Improving Tuberculosis Prognosis with Benchmarked Machine Learning Models
  Tuberculosis remains a considerable cause of morbidity and mortality in several poor and middle-income countries. When a patient is diagnosed with tuberculosis, healthcare providers must select most appropriate treatment tailored to patient's unique situation …
  crossref Muhammad Azhar Javaid 2026-01-03T12:36:06Z 置信度 0.82 medicineintensive care medicinehealth caremedlinedisease
• Machine Learning for High Sigma Analog Designs (Invited)
  Monte Carlo simulations have been the gold standard for assessing parametric yields of analog, mixed signal, and RF circuits as they offer one of the most direct representations of the variation induced by semiconductor manufacturing. However, Monte Carlo anal…
  crossref Srinivas Jallepalli 2024-11-06T18:37:40Z 置信度 0.82 cs.lgstat.mlartificial intelligencecomputer sciencemachine learning
• Machine Learning Molecular Trends
  The parameterization process will require much data, either from experiments or from ab initio calculations, as input for the simulation model. Generating billions of system configurations during a simulation requires evaluating an even more significant number…
  crossref Caroline Desgranges, Jerome Delhommelle 2023-12-13T13:35:51Z 置信度 0.79 artificial neural networkconsciousnesscs.neneuromorphic computingconvolutional neural network
• Choice of Basis for Laplace Approximation
  crossref David J.C. MacKay 2002-12-22T05:04:10Z 置信度 0.55
• Determining Arguments of Invariant Functional Descriptions
  crossref Mieczyslaw M. Kokar 2003-04-04T16:57:10Z 置信度 0.55
• Semantic Clone Detection Using Machine Learning
  If two fragments of source code are identical to each other, they are called code clones. Code clones introduce difficulties in software maintenance and cause bug propagation. In this paper, we present a machine learning framework to automatically detect clone…
  crossref Abdullah Sheneamer, Jugal Kalita 2017-02-07T20:39:53Z 置信度 0.78 cs.aics.lgcs.cvcs.clcomputer and information sciences
• Machine Learning Approaches for Adaptive Forecasting Systems
  Adaptive forecasting systems have become essential for analyzing dynamic and uncertain real-world data, where traditional static forecasting models often fail due to changing patterns, concept drift, and non-stationary conditions. Machine learning techniques, …
  crossref Yuki Nakamura 2026-07-27T10:58:38Z 置信度 0.82 computer scienceartificial intelligencecs.lgmachine learningcomputer and information sciences
• Uncovering Gaps: Dietary Influence and Machine Learning in Hypertension and Comorbidities
  Dear Editor, We read with great interest the recent article by Zhang et al., “Diabetes Mellitus and Hyperlipidemia Status Among Hypertensive Patients in the Community and Influencing Factors Analysis of Blood Pressure Control,” which provides valuable insights…
  crossref Javeria Akhter, Javed Iqbal 2025-05-23T12:59:17Z 置信度 0.82 medicinepsychologycomputer sciencebusinessbiotechnology
• Sensor-level MEG combined with machine learning yields robust classification of mild traumatic brain injury patients
  Objective Diagnosis of mild traumatic brain injury (mTBI) is challenging despite its high incidence, due to the unspecificity and variety of symptoms and the frequent lack of structural imaging findings. There is a need for reliable and simple-to-use diagnosti…
  crossref Juho Aaltonen, Verna Heikkinen, Hanna Kaltiainen, Riitta Salmelin 等 2023-06-30T11:47:27Z 置信度 0.79 medicinebrain-computer interfaceelectroencephalographyphysical medicine and rehabilitationcs.lg
• Machine Learning and the Role of IoT in Health Informatics
  The innovations brought by Industry 4.0 to health informatics and the challenges encountered are discussed. Industry 4.0 initiates a new era in the healthcare sector through the integration of technologies like IoT, machine learning, cloud computing, and big d…
  crossref Burak Taşci 2024-10-02T15:32:01Z 置信度 0.82 businesshealth caredata sciencecomputer scienceengineering
• What Is Machine Learning?
  The first Checkers program from machine learning pioneer Arthur Samuel debuted in 1956, demonstrating artificial “intelligence” capabilities. Since then, not only has the application of artificial intelligence grown, there is now a velocity, volume, and variet…
  crossref Arjun Panesar 2019-02-04T05:24:47Z 置信度 0.79 artificial intelligencebig datadeep learningcomputer sciencecs.lg
• Create Prediction Model using Microsoft Azure Machine Learning Studio
  crossref 2021-03-19T05:40:31Z 置信度 0.64
• Quantitative Trading Method based on Neural Network Machine Learning
  Quantitative trading plays an essential role in the investment field with its advanced mathematical models for computer-aided trading of investment strategies. The artificial neural network algorithm is the trading algorithm with the largest amount of funds ma…
  crossref Weinan Weng 2022-08-19T19:38:41Z 置信度 0.79 artificial neural networkcs.lgcs.neconvolutional neural networkcomputer science
• "Personalized Medicine: Predictive Analytics for Drug Response Using Machine Learning Models"
  Personalized medicine represents a transformative approach in healthcare, enabling tailored therapeutic interventions based on individual patient characteristics. Predictive analytics powered by machine learning (ML) has emerged as a cornerstone of this paradi…
  crossref Diganta Bhattacharyya 2026-06-18T11:06:12Z 置信度 0.82 computer scienceartificial intelligencemedicinedata sciencemachine learning