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• Table 6: Machine learning evaluation metrics.
  crossref 2021-01-25T04:22:03Z 置信度 0.70
• Machine Learning
  Traditional books on machine learning can be divided into two groups- those aimed at advanced undergraduates or early postgraduates with reasonable mathematical knowledge and those that are primers on how to code algorithms. The field is ready for a text that …
  crossref Stephen Marsland 2018-07-02T10:54:57Z 置信度 0.70
• Drug Design with Machine Learning
  crossref 2011-08-29T16:20:21Z 置信度 0.70
• Figure 8: Machine learning model accuracy %.
  crossref 2024-11-11T03:41:02Z 置信度 0.70
• Probability Theory in Machine Learning
  crossref 2012-04-05T06:35:16Z 置信度 0.70
• Machine Learning for IT Security
  crossref 2012-02-07T13:44:39Z 置信度 0.70
• Machine Learning, Ensemble Methods in
  crossref 2011-08-29T12:20:21Z 置信度 0.70
• Figure 7: Machine Learning method result.
  crossref 2021-03-11T05:29:17Z 置信度 0.70
• Supplemental Information 2: Machine Learning Data
  crossref 2021-05-18T05:21:46Z 置信度 0.70
• Figure 5: Machine learning algorithms used.
  crossref 2019-11-11T03:57:35Z 置信度 0.70
• Figure 5: Machine learning (SVM) flowchart.
  crossref 2026-03-11T08:50:59Z 置信度 0.70
• Machine Learning Prediction for Reservoir Permeability
  This chapter explores the application of machine learning ( ML ) techniques as an efficient alternative for permeability estimation, leveraging well log data to model complex nonlinear relationships. Various ML methods are discussed and compared, including art…
  crossref Mohammed Fathy El-Amin 2026-03-06T14:09:53Z 置信度 0.70
• Machine Learning
  crossref Bernd Heesen 2024-09-19T18:35:22Z 置信度 0.70
• Machine Learning as a Batch Process
  This chapter investigates using batch processing to mine and learn from larger amounts of data instead of streaming data. It covers using Hadoop, Sqoop, and Pig for large-scale batch processing; these enable large data sets to be processed with ease. The chapt…
  crossref 2015-08-19T14:37:30Z 置信度 0.70
• Membrane technology and machine learning
  crossref Kiran Mustafa, Mashallah Rezakazemi, Rao Muhammad Mahtab Mahboob 2025-09-27T07:16:40Z 置信度 0.70
• Introduction to machine learning and Python
  crossref Hoss Belyadi, Alireza Haghighat 2021-04-23T14:18:26Z 置信度 0.70
• Predicting Mental Health in Employees and Students Using Machine Learning and Wearable Data
  crossref Tailiang Liu 2026-07-19T13:55:48Z 置信度 0.70
• Structural health monitoring of exterior beam–column subassemblies through detailed numerical modelling and using various machine learning techniques
  Structural health monitoring of beam–column joints is paramount, as they are critical load-carrying components of reinforced concrete buildings. Evaluating the ultimate joint shear capacity and failure modes of beam–columns, especially in seismic events, is a …
  crossref Giuseppe Santarsiero, Mayank Mishra, Manav Kumar Singh, Angelo Masi 2021-10-25T21:48:10Z 置信度 0.70
• Predicting Thyroid Cancer Recurrence Using Machine Learning: An Artificial Intelligence Approach to Clinical Oncology
  Background of study: Differentiated thyroid cancer (DTC) accounts for most thyroid malignancies and has favorable survival outcomes, yet up to 30% of patients experience recurrence, placing strain on follow-up systems in resource-limited settings. Conventional…
  crossref Joy Aifuobhokhan, Ahmad Khalid Hussain, Chijioke Cyriacus Ekechi, Aisha Olasunbo Olanrewaju 等 2025-11-05T03:05:36Z 置信度 0.70
• Applications of Machine Learning and Deep Learning Models in Brain Imaging Analysis
  Brain imaging is an umbrella term including many non-invasive techniques that objectively monitor brain function. Such monitoring leads to understanding how the brain works by presenting selected stimuli. More importantly, brain function monitoring allows phys…
  crossref Alwin Joseph, J Chandra, Bonny Banerjee, Madhavi Rangaswamy 等 2024-01-16T20:36:37Z 置信度 0.70
• Machine Learning for Spectrum Access and Sharing
  This chapter focuses on online learning algorithms that were developed for dynamic spectrum access (DSA), in which a cognitive user aims to learn the occupancy of the spectrum in the presence of external users to improve the spectral usage. The focus is thus o…
  crossref Kobi Cohen 2019-12-13T21:26:07Z 置信度 0.70
• Machine Learning
  crossref Achim Zielesny 2011-07-25T14:20:24Z 置信度 0.70
• Machine Learning Fundamentals for Autonomous Systems
  Machine learning plays a critical role in the development of autonomous systems, allowing them to interpret data, make decisions, and adapt to complex environments without human involvement. This chapter investigates the fundamental principles of machine learn…
  crossref S. Sarika, K.V. Meenatchi, P.B. Tintu 2026-03-19T09:20:51Z 置信度 0.70
• Algorithmic red teaming approaches to secure LLMs
  Algorithmic red teaming for Large Language Models (LLMs) is a crucial practice for proactively ensuring their safety and robustness. This process involves using an LLM as an adversary to test the vulnerabilities of a target LLM, which is essential for identify…
  crossref Shaurya Jauhari 2025-12-27T16:24:01Z 置信度 0.70
• Conflict Resolution as Discovery in Particle Physics
  crossref Sakir Kocabas 2003-04-04T16:55:36Z 置信度 0.70
• Chapter 6: Machine Learning Classifiers with GPT-4
  crossref 2024-06-04T02:00:52Z 置信度 0.70
• Correlation Clustering
  crossref Nikhil Bansal, Avrim Blum, Shuchi Chawla 2004-06-25T21:08:21Z 置信度 0.70
• C3-4: An Algorithm to Combine Machine Learning and Structured Data to Automate De-identification of Clinical Text
  Background/Aims Clinical text is an important resource for research. To maintain patient privacy when researching this text, we use de-identification. The hiding in plain sight (HIPS) method is promising; it replaces personally identifiable information (PII) w…
  crossref D.-T. Tran, S. Halgrim, D. Carrell 2014-10-28T19:51:55Z 置信度 0.70
• Apprenticeship Learning
  crossref 2010-12-29T17:36:36Z 置信度 0.70
• Generative Learning
  crossref 2010-12-29T17:43:13Z 置信度 0.70
• Statistical Learning Theory
  This self-contained introduction to machine learning, designed from the start with engineers in mind, will equip students with everything they need to start applying machine learning principles and algorithms to real-world engineering problems. With a consiste…
  crossref 2023-01-24T19:05:52Z 置信度 0.70
• Preoperative PET/CT phenotype of gastric-type endocervical adenocarcinoma: integrated morphological, metabolic, serological, and explainable machine-learning analysis.
  Gastric-type endocervical adenocarcinoma (GAS) is an aggressive, non-HPV-associated cervical adenocarcinoma that is often difficult to recognize preoperatively. This study aimed to characterize the integrated PET/CT phenotype of GAS and evaluate whether morpho…
  pubmed Wang Y, Su Y, Zhang Y, Cai Y 等 2026 Jul 22 置信度 0.82
• Comparative performance of chatgpt and gemini in diagnostic classification and clinical reasoning for open-angle glaucoma: a standardized scenario-based study.
  To evaluate differences in performance between two large language models (LLMs), GPT-5.3 and Gemini 2.5 Pro, in diagnostic classification and clinical reasoning for primary open-angle glaucoma (POAG).
  pubmed Zhang Z, Lu S, Xu Z, Ji K 等 2026 Jul 22 置信度 0.82
• Identification and functional validation of lipid droplet-associated prognostic biomarkers in breast cancer via integrative multi-omics and machine learning approaches.
  Lipid droplet (LD)-associated metabolic reprogramming plays a critical role in breast cancer progression and immune modulation, yet robust prognostic biomarkers and their functional mechanisms remain incompletely understood. This study aimed to identify LD-ass…
  pubmed Yao J, Liu Z, Zhang J, Long X 等 2026 Sep 置信度 0.82
• Effect of cataracts on systemic factor prediction from fundus images.
  To evaluate the effect of cataracts on systemic factor predictions from fundus images by comparing predictive values before and after cataract surgery.
  pubmed Funatsu R, Mihara N, Miyake S, Okamura K 等 2026 Jul 22 置信度 0.82
• Prognostication of Acute Kidney Injury Following Percutaneous Coronary Intervention: A Machine Learning Approach.
  Acute kidney injury (AKI) is a serious complication of percutaneous coronary intervention (PCI) associated with increased mortality and health care costs. Traditional risk scores often rely on intraprocedural variables, limiting their utility for preprocedural…
  pubmed Itelman E, Altman Y, Yacobi B, Rotmensh A 等 2026 Aug 置信度 0.82
• Multimodal Deep Learning and Knowledge-Enhanced Intelligent Decision Support System for Pipeline Embolization Device Size Selection in Intracranial Aneurysm Treatment.
  This study aimed to develop an end-to-end intelligent decision support system, NeurAneuNet, to automate the selection of Pipeline Embolization Device (PED) size and landing zones for intracranial aneurysm treatment, thereby reducing reliance on operator experi…
  pubmed Wen Z, Guo S, Peng Y, Chen Y 等 2026 Jul 置信度 0.82
• Chemical-Sensing Catheters for Long-Term and Personalized Therapeutic Management.
  Long-term intravenous catheterization is vital for delivering chemotherapy to cancer patients and parenteral nutrition to those with intestinal failure, but it inevitably leads to complications, including metabolic disorders, bloodstream infection, liver injur…
  pubmed Li Y, Cao X, Li Q, Liu X 等 2026 Jul 22 置信度 0.82
• Predictive profiles for poor functional improvement and mortality after transcatheter aortic valve replacement. Value of 6-minute walk test and myocardial work analysis.
  Clinical improvement and survival after transcatheter aortic valve replacement (TAVR) remain difficult to predict. Although multiple predictors of both outcomes have been identified, prognostic algorithms for patients undergoing TAVR are not well established.
  pubmed Rychlewski J, Przewlocka-Kosmala M, Marwick TH, Sen J 等 2026 Jul 22 置信度 0.82
• Assessing a large language model for glaucoma knowledge: ChatGPT-5 versus residents.
  To assess the performance of a contemporary large language model (ChatGPT-5) against ophthalmology residents on a standardized set of glaucoma multiple-choice questions.
  pubmed Gobira M, Moreira R, Carvalho Filho FJLG, Carvalho KWP 等 2026 置信度 0.82
• Predicting gingival embrasure risk after invisible orthodontics using multimodal data and machine learning.
  To develop and validate a risk prediction model for gingival embrasures after clear aligner therapy using multimodal oral data.
  pubmed Wang H, Shi H, Fan L, Sun Z 等 2026 Jul 22 置信度 0.82
• AI Risk Prediction Tools for Autologous Breast Reconstruction.
  Autologous breast reconstruction offers patients a durable and natural-appearing option after mastectomy. However, complication risks include flap loss, infection, and delayed wound healing. This study developed both traditional statistical and machine learnin…
  pubmed Chen J, Gabay A, Hassan AM, Graziano FD 等 2026 Jul 22 置信度 0.82
• A stacking based deep learning framework integrating random search neural architecture search for meniscus tear diagnosis.
  Accurate and rapid diagnosis of meniscal tears is crucial for effective management of sports-related injuries and degenerative knee disorders. Magnetic resonance imaging (MRI) is widely used for meniscus evaluation; however, manual interpretation is time-consu…
  pubmed Seyyarer E, Genç H, Ayata F 2026 Aug 置信度 0.82
• Regional Inequities in Metabolic Dysfunction-associated Steatotic Liver Disease Burden and Care Quality in High-burden Settings: Implications for Health Systems.
  Metabolic dysfunction-associated steatotic liver disease (MASLD) is increasing rapidly, yet regional differences in burden and care quality remain unclear. This study aimed to compare regional incidence, mortality, and disability; evaluate care quality; identi…
  pubmed Zhang K, Kan C, Sheng S, Xu W 等 2026 Jun 28 置信度 0.82
• A Multi-omics and Machine Learning Framework Identifies Plasma SBDS as a Causal Biomarker and Therapeutic Target in Primary Sclerosing Cholangitis.
  Primary sclerosing cholangitis (PSC) is an immune-mediated cholestatic liver disease. Its molecular etiology remains poorly defined, hindering the development of mechanism-based diagnostics and therapies. Therefore, this study aimed to identify key molecular d…
  pubmed Cheng P, Qiang Y, Sun Y, Duan B 等 2026 Jun 28 置信度 0.82
• Lipidomic Profiling and Biological Aging in Patients with Coronary Microvascular Dysfunction.
  Coronary microvascular dysfunction (CMD) was frequently encountered in patients with angina in the absence of epicardial coronary stenosis. CMD was associated with adverse outcomes while the etiology was unclear.
  pubmed Lu D, Deng L, Wang Z, Hu Y 等 2026 置信度 0.82
• Predicting cancer treatment outcomes using machine learning enabled clinical decision support systems.
  Cancer treatment poses significant challenges due to variability in patient responses, disease progression, and therapy outcomes. Traditional decision-making frameworks often fall short in integrating complex data streams, underscoring the need for intelligent…
  pubmed Hossain A, Rashid MM, Alam T, Riipa MB 等 2026 Jan-Dec 置信度 0.82
• Comparative evaluation of the aggregate index of systemic inflammation (AISI) and its modified version for early detection of central line-associated bloodstream infection: a pilot study using machine learning techniques.
  Central line-associated bloodstream infections (CLABSI) are a common and serious problem in critically ill patients; their early detecting is challenging. This study evaluated the predictive ability of the aggregate index of systemic inflammation (AISI) and it…
  pubmed Anand G, Priyadarshi K, Kumari B, Tiewsoh JBA 等 2026 置信度 0.82
• Integrating clinical decision support systems, nursing vigilance, and physician prescribing patterns to reduce preventable adverse drug events: a structured evidence-based narrative review on human-AI interface in medication safety.
  Preventable adverse drug events (ADEs) remain a major source of hospital morbidity, mortality, and healthcare costs worldwide. Clinical decision support systems (CDSS) integrated into electronic health records (EHRs) were developed to reduce unsafe prescribing…
  pubmed Alruwaili MF, Paul-Chima UO, Nneoma UC 2026 置信度 0.82
• Closed loop construction of hypoglycemia risk management for high risk neonates in mother infant rooming in settings: a retrospective study with an embedded clinical decision support system.
  To evaluate the effectiveness of an intelligent clinical decision support system (CDSS) for neonatal hypoglycemia management in mother-infant rooming-in settings, and to dissect the differential hypoglycemia risk conferred by individual high-risk factors and t…
  pubmed Chen L, Shao H, Yu B, Wang M 等 2026 置信度 0.82
• An explainable machine learning framework for accurate prediction of postoperative anterior chamber depth in highly myopic cataract surgery.
  To develop and validate machine learning models for predicting postoperative anterior chamber depth (ACD) in highly myopic cataract patients based on preoperative biometric parameters.
  pubmed Yang Y, Cui H, Gao J, Wang Y 等 2026 置信度 0.82
• A novel study to calculate immune-aging from peripheral blood T lymphocyte subsets and their mitochondrial parameters in healthy Chinese subjects.
  Immunosenescence is a process in which the body's immune function declines with age, which is associated with the increased risk of infection, tumors, and other diseases. Traditional biological age assessment is difficult to fully reflect the changes in immune…
  pubmed Gan G, Guo P, Li X, Zhang S 等 2026 置信度 0.82
• Artificial Intelligence and Machine Learning-Based Triage Systems in Emergency Departments: A Systematic Review of Predictive Performance and Clinical Outcomes.
  Emergency department (ED) triage systems are essential for prioritizing patients based on clinical urgency, yet traditional methods are subject to inter-observer variability and limited predictive accuracy. Artificial intelligence (AI) and machine learning (ML…
  pubmed Mohamed N, Mohammed Ibrahim AA, Shahid N, Alhussein Alamass SI 等 2026 Jun 置信度 0.82
• Integration of periodontal pathogens and inflammatory mediators in saliva as biomarkers for periodontitis.
  Periodontitis pathogenesis is driven by oral microbiome dysbiosis and dysregulated host immune responses. This cross-sectional study characterized salivary microbiome and inflammatory mediator profiles to identify candidate biomarkers distinguishing periodonta…
  pubmed Titusson C, Lundmark A, Soares RRG, Damdimopoulos A 等 2026 置信度 0.82
• Anthropometry-adjusted TyG indices predict diabetes, graft failure, and mortality in kidney transplant recipients.
  The triglyceride-glucose (TyG) index is a widely used surrogate marker of insulin resistance and associated with cardiometabolic outcomes. However, the comparative prognostic value of TyG-derived indices, particularly those incorporating anthropometric measure…
  pubmed Xiong J, Szili-Torok T, Özyilmaz ÖT, Xu W 等 2026 Aug 置信度 0.82
• ATF3 and HNF4A: an oxidative phosphorylation and cholesterol homeostasis-associated diagnostic and therapeutic repurposing framework target for metabolic dysfunction-associated steatohepatitis patients.
  Metabolic dysfunction-associated steatohepatitis (MASH) is hepatic steatosis. Oxidative phosphorylation and cholesterol homeostasis (OC) plays a key role in the onset and progression of MASH. Hence, deeper understanding of OC in MASH can shed light on the clin…
  pubmed Zeng G, Zhao Q, Jiang L, Xie D 等 2026 置信度 0.82
• Primary Graft Dysfunction After Lung Transplantation: A Temporal Classification and Machine Learning Clustering.
  Primary graft dysfunction (PGD) is a major cause of morbidity and mortality after lung transplantation (LTx). PGD is graded at static time points, limiting insight into its temporal dynamics. Statistical risk-factor analysis may overlook the multifactorial com…
  pubmed Özsoy B, Vercauteren B, Van Slambrouck J, Vanluyten C 等 2026 Aug 置信度 0.82
• Are Real-World Mobility Patterns Early Indicators of COPD Onset? Insights from Wrist-Worn Sensors.
  Chronic Obstructive Pulmonary Disease (COPD) is a leading cause of disability and death worldwide. Early identification remains challenging, as existing prediction models largely rely on clinic-based assessments and self-report measures that are resource-inten…
  pubmed Fernandez N, Wong AYL, Brodie MA, Van Schooten KS 等 2026 置信度 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.70
• 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 0.70
• 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 0.70
• 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 0.70
• 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 0.70
• 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 0.70
• 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 0.70
• 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 0.70
• 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 0.70