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• Machine learning for diagnosing non-ST-segment elevation myocardial infarction: a derivation and validation study.
  Previously developed machine-learning (ML)-based decision support tools for patients presenting with suspected non-ST-segment elevation myocardial infarction (NSTEMI) remain proprietary, limiting public accessibility and clinical adoption.
  pubmed Champetier A, Lopez-Ayala P, Reich C, Boeddinghaus J 等 2026 Jul 置信度 0.93 internal medicinemedicineintensive care medicinemedical physicsrehabilitation
• Artificial Intelligence in Orthodontics: From Laboratory Benchmarks to Clinical Care.
  Artificial intelligence (AI) is now used in routine orthodontic practice, not only in research, but how well it works depends heavily on the application. This narrative review synthesises peer-reviewed studies published between 2019 and early 2026 across seven…
  pubmed Alkadhi OH 2026 Jun 置信度 0.96 medicineartificial intelligencecs.aimedlinecomputer science
• A Global and Local SHAP-Driven Interpretable Framework for Early Hospital Admission Prediction With Machine Learning at Emergency Department Triage.
  Emergency department (ED) crowding and constrained hospital resources drive the need for early risk stratification to efficiently identify patients requiring inpatient admission or escalation of care. Machine learning (ML) models are promising as helpful tools…
  pubmed Brown AE, Marostica CW, Hodgson NR, Martini WA 2026 Jun 置信度 0.96 cs.lgartificial intelligenceinterpretabilitycs.aimedicine
• Explainable machine learning for perioperative surgical site infection risk enrichment after operative treatment of closed pilon fractures: a multicenter retrospective study with external validation.
  Surgical site infection (SSI) remains a major complication after operative treatment of closed pilon fractures. Prediction tools may help identify patients who warrant closer perioperative wound surveillance, but externally validated and clinically interpretab…
  pubmed Deng Z, Zhao F, Zhang Y, Zhang T 等 2026 置信度 0.96 internal medicinemedicineintensive care medicinediseasemedical physics
• DeepHeptox: An Interpretable Deep Learning Model for Multi-Endpoint Hepatotoxicity Prediction of Chemical Compounds.
  Hepatotoxicity represents a major adverse outcome of chemical exposure, as the liver plays a central role in xenobiotic metabolism and detoxification. Accurate prediction of hepatotoxicity is therefore essential for drug development and chemical safety assessm…
  pubmed Luo M, Wang Q, Wang Y, Li F 等 2026 Aug 10 置信度 0.96 medicinecs.lgdrug discoveryq-bio.qmbiology
• Intelligent Nanomedicine: AI-Driven Smart Carrier Design for Precision Skin Cancer Therapy.
  Skin cancer, one of the most common malignancies globally, continues to present major therapeutic hurdles such as limited drug penetration, high systemic toxicity, and tumor recurrence. Nanomedicine has emerged as a powerful approach to overcome these challeng…
  pubmed Meshram N, Vinchurkar K, Borse L, Singh S 2026 Jul 16 置信度 0.96 computer scienceartificial intelligencemedicineengineeringtransformative learning
• Intelligent Orthopedics: Machine Learning in Diagnosis of Bone Disease, Implants, and Bone Health Monitoring.
  Bone regeneration in orthopedics is a great challenge, as efficient recovery affects patient's quality of life. Common methods encounter different limitations regarding diagnosis, implantation, and bone health monitoring. Recent advances in artificial intellig…
  pubmed Kamaei M, Mohammadi H, Golafshan S, Alehosseini M 等 2026 Jul 19 置信度 0.96 computer sciencemedicineartificial intelligencehealth caremedical physics
• Comprehensive evaluation of angiogenesis-associated genes in papillary thyroid cancer using bulk RNA and single-cell sequencing data.
  The objective of this study is to explore the expression patterns of angiogenesis-related genes in papillary thyroid cancer (PTC) to enhance understanding of the molecular mechanisms underlying angiogenesis in this malignancy. The findings provide valuable ins…
  pubmed Zhao J, Qin YX, Zhao M, Niu H 等 2026 Jul 19 置信度 0.83 cancertraditional chinese medicineknowledge managementmicrobiologymedline
• A clinically interpretable model for predicting pharyngocutaneous fistula after total laryngectomy.
  Pharyngocutaneous fistula (PCF) is a frequent complication following total laryngectomy. While various risk models exist, their practical utility is often limited by poor calibration and a lack of guidance on modifiable risk factors. This study aimed to develo…
  pubmed Hu G, Han L, Cai L, Lu S 等 2026 Jul 19 置信度 0.93 medicinerisk analysissystematic reviewmedical physicsinternal medicine
• Combining transvaginal ultrasound radiomics with clinical-ultrasound semantic features for the identification of high-risk endometrial lesions.
  Preoperative risk stratification of high-risk endometrial lesions remains a clinical challenge. This study aimed to preliminarily explore an integrated machine learning approach combining transvaginal ultrasound (TVUS) radiomics, clinical indicators, and ultra…
  pubmed Yao X, Ye X, Chen L, He Y 等 2026 Jul 20 置信度 0.93 intensive care medicinediseaseinternal medicinemedical physicsinterpretability
• Bioinformatics reveals the prognostic potential of manganese metabolism-related genes in lung adenocarcinoma.
  Manganese metabolism may be involved in the malignant progression of lung adenocarcinoma (LUAD). Clarifying the roles of manganese metabolism-related genes (MMRGs) in LUAD may provide potential therapeutic targets for LUAD treatment. Mendelian randomization an…
  pubmed Zha J, Liu X, Gao S, He J 等 2026 Jul 20 置信度 0.96 medicinebiologycancercell biologypharmacology
• Predictive modeling of fluid status in hemodialysis: model development and internal validation using the MONitoring dialysis outcomes (MONDO) global database.
  Optimized fluid management is crucial in dialysis care because extracellular volume overload drives adverse cardiovascular outcomes. At the same time, comorbidities such as inflammation and protein energy wasting lead to decreased muscle mass and intracellular…
  pubmed Yueh SH, Raimann J, Canaud B, Zhou M 等 2026 Dec 置信度 0.86 medicineinternal medicineintensive care medicinescience policydisease
• Early Prediction of Critical Care Interventions From Pediatric Emergency Department Triage.
  Most pediatric emergency departments (EDs) in the United States use Emergency Severity Index (ESI) system to triage patients. Because the 5-level classification provides limited risk stratification, this study aims to improve patient prioritization by developi…
  pubmed Ha T, Kappy B, Chamberlain JM, McKinley KW 2026 Aug 1 置信度 0.83 medicineintensive care medicineinternal medicinepsychological interventionmental health
• Deep learning-enhanced zero echo time MRI for femoral cortical bone quantification: A technical validation against CT.
  This study compared quantitative measurements of femoral cortical bone between zero echo time magnetic resonance images (oZTEo) and computed tomographic (CT) images as proof-of-concept for algorithm performance in subjects referred to our clinic for femoroacet…
  pubmed Koretsky EG, Singh D, Consolini J, Mandava S 等 2026 Nov 置信度 0.96 medicinebiological sciences not elsewhere classifiedinternal medicineconvolutional neural networkscience policy
• Hierarchically ordered ERGO-L-Cys flower-like nanospheres on screen-printed electrodes for electrochemical immunosensing of cow's milk specific IgE with machine learning-assisted calibration.
  Cow's milk-specific IgE (sIgE) is a crucial serum biomarker for cow's milk allergy (CMA) in children. However, its low abundance and the scarcity of reference standards have made it challenging to develop effective electrochemical detection platforms for clini…
  pubmed Yang M, Xie C, Gao X, Jiang X 等 2026 Jul 18 置信度 0.96 materials sciencemedicinephysical scienceschemistrycomputer science
• [Overview and conclusions of the STROKE data platform of the National Laboratory for Translational Neuroscience and the associated clinical studies].
  Acute ischemic and hemorrhagic stroke are among the leading causes of mortality and long-term disability worldwide. In addition to the results of randomized clinical trials, registry data reflecting real-world clinical practice play a key role in evaluating th…
  pubmed Schranz D, Fehér G, Jozifek E, Karádi Z 等 2026 Jul 19 置信度 0.96 medicinephysical medicine and rehabilitationrehabilitationinternal medicineintensive care medicine
• An evidence informed framework for artificial intelligence in rare breast cancers using small cohort validation synthetic data practices and clinical governance.
  Rare breast cancers represent a clinically important but underrepresented group of malignancies. In this Perspective, rare breast cancers are considered within the broader rare cancer definition of an annual incidence below 6 cases per 100,000 persons, while a…
  pubmed Alshreef BS 2026 Jul 19 置信度 0.96 medicineartificial intelligencehealth caredata sciencecancer
• Development and temporal validation of an interpretable XGBoost model for predicting cardiovascular death in patients with diabetic foot.
  Patients with diabetic foot (DF) have a high risk of cardiovascular (CV) death, yet dedicated risk-prediction tools for this population are lacking. We developed and temporally validated an interpretable machine learning (ML) model for predicting CV death in p…
  pubmed Wan X, Shi T, Liu Q, She Y 等 2026 Jul 17 置信度 0.96 medicineinternal medicineintensive care medicineartificial intelligencemedline
• Artificial Intelligence in Hypertension Management: Promise Must Precede Practice.
  Hypertension remains one of the most important modifiable risk factors for cardiovascular disease worldwide, yet blood pressure control rates remain suboptimal despite advances in diagnosis and treatment. Artificial intelligence (AI) has emerged as a promising…
  pubmed Ghantiwala KR, Kevadiya R, Pentapurthy P, Thakor AR 等 2026 Jun 置信度 0.96 medicinehealth careintensive care medicinemedical physicsinterpretability
• Integrative Bioinformatics Analysis and Machine Learning Reveal TSPAN7 Regulates the Involution of Infantile Hemangioma via NK Cells.
  The involution of infantile hemangioma (IH) involves complex lipid metabolism reprogramming and immune modulation, but the underlying molecular mechanisms remain incompletely understood. This study aimed to identify key lipid metabolism-related genes that may …
  pubmed Bai J, Lin S 2026 置信度 0.93 systematic reviewpsychologymicrobiologyinternal medicinebioinformatics
• Integration of artificial intelligence applications in clinical pharmacy services: A scoping review.
  Artificial intelligence (AI) is increasingly being integrated into healthcare systems, offering new opportunities to enhance the safety, efficiency and effectiveness of clinical pharmacy services. This scoping review aimed to systematically map the current app…
  pubmed Al-Taie A, Abdullah AS, Arueyingho O 2026 Sep 置信度 0.93 health careengineering ethicsdata sciencemedical physicsmedline
• Large Language Models for Traumatic Dental Injuries Across Web-Based and Mobile-Based Interfaces: Assessing Accuracy, Quality, and Temporal Consistency.
  Traumatic dental injuries (TDIs) are frequent in clinical practice and require rapid, guideline-based decisions, yet accessing accurate and reliable information may be challenging. Large language models (LLMs) such as ChatGPT, Gemini, DeepSeek, and Qwen are in…
  pubmed Cekic EC, Kumru M, Yilmaz B, Celikkol B 等 2026 Aug 置信度 0.96 medical educationcs.aicomputer sciencenatural language processingmedline
• Habitat-based imaging and peritumoral radiomics on ultrasound images for predicting lymphovascular invasion in breast invasive ductal carcinoma: a two-center study.
  This study aimed to evaluate the feasibility of employing habitat-based radiomic distributions in ultrasound (US) images to quantitatively characterize intratumoral heterogeneity. It also explored the potential of this approach to predict lymphovascular invasi…
  pubmed Liu T, Zhao G, Wei W, Zhang Q 等 2026 Jul 18 置信度 0.89 medicineinternal medicinebiological sciences not elsewhere classifiedpopulationcancer
• Hypoxia tumor-associated macrophages facilitate hepatocellular carcinoma metastasis via uPA-uPAR pathway.
  Hepatocellular carcinoma (HCC) arises within a hypoxic and immunosuppressive tumor microenvironment (TME), where tumor-associated macrophages (TAMs) constitute a major immune population. The impact of hypoxia on TAM functional heterogeneity and their contribut…
  pubmed Wang Y, You X, Luo X, Huang W 等 2026 Jul 18 置信度 0.83 ai governancesocial and behavioral sciencesecosystemhydrogeninternal medicine
• Decoding dry eye disease based on bioinformatics and in vitro experimental: the role of immune responses and natural product intervention.
  Dry eye disease (DED), a prevalent ocular condition, has seen rising incidence rates. Aberrant inflammation and immune dysregulation are key pathogenic factors in DED. However, the underlying mechanisms linking autoimmunity to DED therapy remain incompletely u…
  pubmed Long X, Liu G, Liu P, Jiang P 等 2026 Jul 18 置信度 0.96 medicinetraditional chinese medicinecancertraditional medicinedisease
• Interpretable, internally validated prognostic modelling of cumulative clinical pregnancy in women with diminished ovarian reserve.
  To develop and internally validate an interpretable prognostic model for cumulative clinical pregnancy in women with diminished ovarian reserve (DOR), and to explore, as a hypothesis-generating secondary aim, whether protocol-associated pregnancy rates differ …
  pubmed Wu H, Huang Q, Long Y, Jiang L 等 2026 Jul 18 置信度 0.89 medical physicsmedlinemulti-agent systemspharmacologydisease
• AMIUgraph: analysis and modeling of interactions for utility-driven benchmarking of graph-based models in healthcare.
  Graph-based machine learning approaches, including Knowledge Graph Embedding (KGE) methods and Graph Neural Networks (GNNs), have emerged as powerful tools for modeling complex biomedical data. However, a systematic and clinically grounded comparison of these …
  pubmed Sorino P, Bellis A, Malitesta D, Lofù D 等 2026 Jul 18 置信度 0.96 cs.lgcomputer sciencestat.mlinterpretabilityartificial neural network
• Stage-specific predictors of exercise adherence after percutaneous coronary intervention: a prospective multicenter study.
  The efficacy of exercise after Percutaneous Coronary Intervention (PCI) is compromised by poor long-term adherence. Although multiple influencing factors are recognized, their dynamic evolution and relative importance across different stages remain unclear, hi…
  pubmed Xia C, Ji L, Guo H, Du Y 等 2026 Jul 18 置信度 0.89 internal medicinerehabilitationintensive care medicinephysical medicine and rehabilitationpsychological intervention
• Exploratory development of prediction models for pharmacotherapy outcomes in trigeminal neuralgia: a combined analysis based on multi-source data.
  Drug-refractory trigeminal neuralgia (DRTN) represents a formidable challenge in clinical management, with approximately 30%-50% of patients eventually progressing to DRTN. Early identification of high-risk DRTN populations and prediction of the timing of phar…
  pubmed Yang H, Sun B, Li M, Yang X 等 2026 Jul 18 置信度 0.93 medicineintensive care medicinediseaseinternal medicinemedical physics
• Multi-omics and network toxicology prioritize ADAMTS13 as a candidate gene computationally linked to TDCPP targets in hepatocellular carcinoma.
  Tris(1,3-dichloro-2-propyl) phosphate (TDCPP), a widely used organophosphate flame retardant, has been increasingly recognized as a potential environmental risk factor for human cancers. However, its potential association with hepatocellular carcinoma (HCC) an…
  pubmed Liu X, Gong D, Gou T, Chen P 2026 Jul 19 置信度 0.89 medicinepharmacologytraditional chinese medicinebiochemistrytraditional medicine
• Integrating omics and artificial intelligence in pediatric environmental health: tools, challenges, and cohort-based insights.
  Early childhood is a critical developmental period during which exposure to multiple environmental chemicals is common and increasingly recognized as an important determinant of long-term health. However, conventional risk-assessment methods are often poorly e…
  pubmed Al-Saleh I 2026 Jul 18 置信度 0.93 biochemical engineeringmodular designphysical medicine and rehabilitationwearable computerq-bio.mn
• Breaking the norm: population-scale deviations of brain structure in depression and anxiety.
  Structural brain alterations associated with depression and anxiety are subtle, heterogeneous, and difficult to characterize. We applied autoencoder-based normative modeling to contrastively learned structural MRI representations from two large population-base…
  pubmed Wiegert J, Marty-Lombardi S, Oweda J, Lenz E 等 2026 Jul 18 置信度 0.96 psychologymedicinesocial and behavioral sciencesneurosciencepopulation
• Single cell and bulk transcriptomics reveal metabolic reprogramming biomarker signatures during extracorporeal membrane oxygenation for cardiogenic shock.
  Cardiogenic shock (CS) patients receiving extracorporeal membrane oxygenation (ECMO) exhibit profound immune and metabolic disturbances, which may influence early clinical outcomes. However, the transcriptomic features linking metabolic reprogramming, immune-c…
  pubmed Zhou X, Aierken D, Sun L, Chang X 等 2026 Jul 18 置信度 0.96 medicinebiologypsychologycancerbiotechnology
• Machine unlearning as a governance imperative for clinical AI.
  Clinical AI assumes that the influence of training data can persist indefinitely. This premise fails when patients withdraw consent, evidence evolves, or bias is identified. Machine unlearning aims to remove specific data influence without full retraining. We …
  pubmed Porter A, Kirkpatrick E, Garg A, Saratchandran H 等 2026 Jul 18 置信度 0.96 multi-agent systemsai governanceworkflowpsychological interventionintensive care medicine
• Machine learning-based diagnosis of movement disorders using clinical neurophysiology: are we ready?
  pubmed Grippe T 2026 Oct 置信度 0.77
• PatientSpace: A multimodal graph-based latent representation framework for modeling neurodegenerative disease heterogeneity.
  Neurodegenerative diseases such as Alzheimer's disease (AD) and frontotemporal dementia (FTD) exhibit substantial biological and clinical heterogeneity, complicating diagnosis, subtype characterization, and prediction of disease progression. We introduce Patie…
  pubmed Manouvriez D, Kuchcinski G, Lecerf S, Lahousse H 等 2026 Sep 置信度 0.96 medicinediseaseneurosciencecs.lgartificial intelligence
• Model development and feasibility of real-world deployment of multimodal input-based subtyping of depression in tele-counseling for scalable mental health assessment.
  The rapid growth of tele-counseling and the use of lay counselors in high-volume, low-resource mental health services has created a need for scalable tools for early detection and triage. Effective personalization now requires stratifying individuals by domina…
  pubmed Ashwin Francis AJ, Raza A, Patel N, Gajbhiye R 等 2026 Sep 置信度 0.96 computer sciencemedicinecs.aiartificial intelligencebiological sciences not elsewhere classified
• Clinically meaningful risk factors for recurrence in T1 colorectal cancer treated with endoscopic resection alone identified by unsupervised machine learning: a multicenter study.
  Identifying patients at high risk for recurrence after endoscopic resection of T1 colorectal cancer (CRC) remains challenging. This study aimed to identify recurrence risk subtypes and develop an interpretable risk stratification framework.
  pubmed Zhou X, Togashi K, Zhu X, Kajiwara Y 等 2026 Aug 12 置信度 0.93 internal medicineintensive care medicinecancermedicinedisease
• Genetic and systems-level regulation of cancer metabolism: From metabolic reprogramming to AI-driven precision oncology.
  The metabolic activities of cancer cells undergo complete transformation because they need to maintain their growth while resisting metabolic challenges and environmental dangers from their tumour surroundings. The metabolic changes that occur in cells depend …
  pubmed Ajay N, Anilkumar AS, Veerabathiran R 2026 Aug 置信度 0.96 artificial intelligencebiologypsychologyneurosciencesynthetic biology
• Applications of artificial intelligence and machine learning in assisted reproductive technology: Focus on In Vitro fertilization (IVF) and intracytoplasmic sperm injection (ICSI).
  In vitro fertilization (IVF) and intracytoplasmic sperm injection (ICSI) are two medical treatments intended to treat infertility that are included in the category of assisted reproductive technology (ART). In view of the growing incidence of infertility and t…
  pubmed Jamshidvand H, Mohsennezhad A, Salehisedeh N, Riahi A 等 2026 Jul 11 置信度 0.96 medicineartificial intelligencecomputer sciencedata sciencemedical physics
• Genotypic-phenotypic concordance of Pasteurella multocida isolated from bovine respiratory disease cases.
  Pasteurella multocida is a respiratory pathogen that is frequently isolated from cattle suffering from bovine respiratory disease (BRD), a leading cause of morbidity and mortality on modern-day cattle farms. Treatment involves the use of antimicrobials which h…
  pubmed Sheets TR, Ellis AC, Wickware CL, Gribskov M 等 2026 Sep 置信度 0.96 medicinebiologypharmacologybiotechnologycomputational biology
• Applied Identity Physics: AIM Due Diligence and FCA Category 3 Reckless Disregard for Corpus-Adjacent Research
  Applied Identity Physics: AIM Due Diligence and FCA Category 3 Reckless Disregard for Corpus-Adjacent Research Architect: HIGHTISTIC (Russell Vernon Trent III) Coordinate: [9,9,8,4] · Origins Series · Paper 4 · v1.0.6 Source prediction: Origins Series Paper 3 …
  datacite Trent, Russell 2026 置信度 0.68
• The "how" over the "who": A machine learning approach to understanding clinical judgment in acute suicide risk assessment
  Background: Suicide is a pressing public health crisis in Bogotá, Colombia. Despite escalating rates, a gap exists in data-driven research using localized, real-world clinical data. This study aimed to train and interpret a machine learning model to predict ac…
  datacite Jaramillo-Gutiérrez, Juan Camilo 2026 置信度 0.77 Suicidio en BogotáMachine LearningPredicción de riesgo agudoMétodos de alta letalidadDatos epidemiológicos
• hypertopos
  hypertopos is a Python library that transforms relational data into a geometric space where structure, anomalies and change become directly observable — without training machine learning models. Every entity gets a coordinate derived from its typed relationshi…
  datacite Karol Kędzia 2026 置信度 0.79 geometric data analysisanomaly detectionunsupervised learningrelational datadrift detection
• Evaluating AI Tools for COPD Management: NLP-Based Identification of Exacerbations in Local EHRs
  In this study we evaluate the performance of classical machine learning models, and transformer?based models (BioClinicalBERT and large language models (LLMs) for the automatic identification of COPD exacerbations using unstructured clinical texts from Colombi…
  datacite Campos Lozano, Jonathan, Ruiz Rodriguez, Nini Yohana, Jaimes Fernandez, Diego Alejandro, Jaimes Fernandez, Diego Alejandro 等 2025 置信度 0.77 Chronic Obstructive Pulmonary Disease (COPD)Exacerbation DetectionBioClinicalBERTClinical RecordsNatural Language Processing
• Cone density estimation in AOSLO images using image processing and deep learning
  In ophthalmology, early detection of degenerative diseases in the eye is crucial, however, many times conventional clinical cameras do not allow quantification of retinal cell loss and, in addition, manual analysis of these images is inefficient and poorly aut…
  datacite Cerda Cortez, Nicolay Agustin 2026 置信度 0.77 AOSLODensidad de conosAprendizaje profundo livianoEstimación automatizadaDespliegue clínico
• Processed Dataset for: Cascaded Machine Learning Integration of Biochemical, Molecular, and Clinical Features for Multi-Class Acute Coronary Syndrome Classification
  Acute Coronary SyndromeMachine LearningLightGBMlncRNACardiovascular Disease
  datacite El-Attar, Noha 2026 置信度 0.68
• Processed Dataset for: Cascaded Machine Learning Integration of Biochemical, Molecular, and Clinical Features for Multi-Class Acute Coronary Syndrome Classification
  Acute Coronary SyndromeMachine LearningLightGBMlncRNACardiovascular Disease
  datacite El-Attar, Noha 2026 置信度 0.68
• A Multimodal Artificial Intelligence Framework for Diabetes Risk Prediction and Diabetic Retinopathy Classification using Clinical and Retinal Data
  Diabetes mellitus is a major chronic disease for which timely risk identification and screening can support earlier clinical intervention. Artificial intelligence provides opportunities to analyse both structured clinical measurements and retinal fundus images…
  datacite Shubhangi Ojha 2026 置信度 0.79 Artificial intelligencediabetes predictiondiabetic retinopathyretinal fundus imagingResNet-50
• A Multimodal Artificial Intelligence Framework for Diabetes Risk Prediction and Diabetic Retinopathy Classification using Clinical and Retinal Data
  Diabetes mellitus is a major chronic disease for which timely risk identification and screening can support earlier clinical intervention. Artificial intelligence provides opportunities to analyse both structured clinical measurements and retinal fundus images…
  datacite Shubhangi Ojha 2026 置信度 0.79 Artificial intelligencediabetes predictiondiabetic retinopathyretinal fundus imagingResNet-50
• Cognitive Retrain: A Web-Based Cognitive Skill Enhancement and Early Detection System for Children with ASD And Dyslexia
  Early detection and continuous therapeutic intervention are critical for children facing cognitive learning challenges, particularly Autism Spectrum Disorder (ASD) and Dyslexia. Traditional clinical diagnostic methodologies are resource-intensive, highly susce…
  datacite Mr. M. Narsimhulu, K. Guna Sai, G. Gokul Kashyap, Gayathri Mangalarapu 等 2026 置信度 0.79 Machine LearningAutism Spectrum DisorderDyslexiaGamified LearningRetrieval-Augmented Generation
• Cognitive Retrain: A Web-Based Cognitive Skill Enhancement and Early Detection System for Children with ASD And Dyslexia
  Early detection and continuous therapeutic intervention are critical for children facing cognitive learning challenges, particularly Autism Spectrum Disorder (ASD) and Dyslexia. Traditional clinical diagnostic methodologies are resource-intensive, highly susce…
  datacite Mr. M. Narsimhulu, K. Guna Sai, G. Gokul Kashyap, Gayathri Mangalarapu 等 2026 置信度 0.79 Machine LearningAutism Spectrum DisorderDyslexiaGamified LearningRetrieval-Augmented Generation
• External validation of prediction models for induction of labor outcomes: Individual Participant Data (IPD) Meta-Analysis – A study protocol
  This protocol is a systematic review to identify and select robust induction of labor (IOL) outcome prediction models to externally validate selected clinical prediction models. We will use individual participant data (IPD) from published randomised controlled…
  datacite Sofonyas Abebaw Tiruneh, Yanan Hu, Ling Shan Au, Ben W Mol 等 2026 置信度 0.75 Medicine and Health SciencesCeasrean sectionClinical prediction modelInduction of labourMachine learning
• Artificial Intelligence-Enabled Wearable Devices for Cardiovascular Disease Screening, Monitoring, and Intervention: An Umbrella Review of Systematic Reviews
  Background Cardiovascular disease (CVD) remains the top cause of global mortality and imposes heavy chronic disease burden worldwide. In China, the prevalence and mortality of CVD have risen sharply over the past decades, accompanied by younger onset age and m…
  datacite 薛则佩, 丁雄, Maoyi Tian, Ning Tang 等 2026 置信度 0.79 Health Information TechnologyDiseasesCardiologyPublic HealthMedicine and Health Sciences
• Digital Intelligence technology empowers interprofessional collaboration and the well-being of medical social workers: a scoping review on health promotion for medical social workers
  Health and social workers (HSWs) and community health workers (CHWs) are critical to health equity in low- and middle-income countries (LMICs), yet they face persistent knowledge gaps, resource constraints, and limited institutional support. Digital technologi…
  datacite jiyan ma, YUKE DAI, jie kang 2026 置信度 0.79 Clinical and Medical Social WorkMedicine and Health SciencesPublic Affairs, Public Policy and Public AdministrationSocial WelfareMental and Social Health
• A Multi-Omic Signature of Diabetes-Associated Pancreatic Cancer for Predicting Clinical Outcomes and Immunotherapy Response
  This is a fully computational, hypothesis-driven bioinformatics study. We will integrate publicly available transcriptomic, proteomic, metabolomic, and clinical data from PDAC patients with documented diabetes status. The study will involve: Data curation and …
  datacite PAWAN kadwe 2026 置信度 0.77 Medicine and Health SciencesLife Sciencescancer
• Real-World Data Analytics in Biomedical Research
  Real-world data (RWD) -- information collected from routine clinical care, insurance claims, patient registries, wearabledevices, and patient-reported outcomes -- represents an increasingly important complement to randomised controlledtrials in biomedical rese…
  datacite Marco Klein, Oscar Bianchi 2026 置信度 0.76 real-world data; real-world evidence; causal inference; target trial emulation; propensity score; comparative effectiveness; pharmacoepidemiology; observational research
• Real-World Data Analytics in Biomedical Research
  Real-world data (RWD) -- information collected from routine clinical care, insurance claims, patient registries, wearabledevices, and patient-reported outcomes -- represents an increasingly important complement to randomised controlledtrials in biomedical rese…
  datacite Marco Klein, Oscar Bianchi 2026 置信度 0.76 real-world data; real-world evidence; causal inference; target trial emulation; propensity score; comparative effectiveness; pharmacoepidemiology; observational research
• Predictive Modeling of Host–Pathogen Interactions
  Host-pathogen interactions (HPIs) -- the molecular, cellular, and immunological interplay between pathogens and theirhosts -- determine infection outcomes, pathogen virulence, host immune response, and therapeutic vulnerabilities.Predictive modelling of HPIs s…
  datacite Hugo Novak, Anna Garcia, Noah Moreau 2024 置信度 0.76 host-pathogen interactions; protein-protein interactions; infection biology; vaccine design; antimicrobial discovery; immune response; pathogen genomics; structural biology
• Predictive Modeling of Host–Pathogen Interactions
  Host-pathogen interactions (HPIs) -- the molecular, cellular, and immunological interplay between pathogens and theirhosts -- determine infection outcomes, pathogen virulence, host immune response, and therapeutic vulnerabilities.Predictive modelling of HPIs s…
  datacite Hugo Novak, Anna Garcia, Noah Moreau 2024 置信度 0.76 host-pathogen interactions; protein-protein interactions; infection biology; vaccine design; antimicrobial discovery; immune response; pathogen genomics; structural biology
• Validating objective and scalable speech markers of depression across two independent psychiatric cohorts
  Abstract Background Using speech as objective markers for major depressive disorder (MDD) has shown promise, yet their generalizability across clinical settings remains largely unvalidated. Objective This study aimed to validate previously identified speech ma…
  datacite Felix Menne, Felix Dörr, Johannes Tröger, Alexandra König 等 2026 置信度 0.77 MedicineSociologyBiological Sciences not elsewhere classifiedScience PolicyMental Health
• Validating objective and scalable speech markers of depression across two independent psychiatric cohorts
  Abstract Background Using speech as objective markers for major depressive disorder (MDD) has shown promise, yet their generalizability across clinical settings remains largely unvalidated. Objective This study aimed to validate previously identified speech ma…
  datacite Felix Menne, Felix Dörr, Johannes Tröger, Alexandra König 等 2026 置信度 0.77 MedicineSociologyBiological Sciences not elsewhere classifiedScience PolicyMental Health
• A machine learning framework for cost-efficient resource allocation: evidence from HER2-positive breast cancer diagnosis in low-resource settings
  Abstract Accurate identification of HER2-positive breast cancer is essential for treatment planning; however, diagnostic decision-making in resource-constrained healthcare systems is challenged by class imbalance, which can substantially reduce the detection o…
  datacite Hoda Waguih 2026 置信度 0.79 Space ScienceMedicineBiological Sciences not elsewhere classifiedInformation Systems not elsewhere classifiedCancer
• A machine learning framework for cost-efficient resource allocation: evidence from HER2-positive breast cancer diagnosis in low-resource settings
  Abstract Accurate identification of HER2-positive breast cancer is essential for treatment planning; however, diagnostic decision-making in resource-constrained healthcare systems is challenged by class imbalance, which can substantially reduce the detection o…
  datacite Hoda Waguih 2026 置信度 0.79 Space ScienceMedicineBiological Sciences not elsewhere classifiedInformation Systems not elsewhere classifiedCancer
• Privacy-Preserving Federated Learning Framework for ICU Patient Monitoring and Decision Support in Hospitals
  The increasing digitization of healthcare systems has led to the generation of large-scale ICU patient data across hospitals. However, centralized machine learning approaches pose significant privacy risks, limiting data sharing across institutions. This paper…
  datacite Mr. B. Sundaresan, Bernus A, Jayamadhavan V, Sam Benny J Department of Computer Science & Engineering Velammal Institute of Technology, Panchetti, DEPARTMENT OF ARTIFICIAL INTELLIGENCE AND DATA SCIENCE R.M.K. College of Engineering and Technology, MISSILE MAN SCIENTIFIC AND RESEARCH PUBLICATIONS 2026 置信度 0.77 computer sciencecomputer and information sciencesmachine learningartificial intelligencecryptography and security
• Privacy-Preserving Federated Learning Framework for ICU Patient Monitoring and Decision Support in Hospitals
  The increasing digitization of healthcare systems has led to the generation of large-scale ICU patient data across hospitals. However, centralized machine learning approaches pose significant privacy risks, limiting data sharing across institutions. This paper…
  datacite Mr. B. Sundaresan, Bernus A, Jayamadhavan V, Sam Benny J Department of Computer Science & Engineering Velammal Institute of Technology, Panchetti, DEPARTMENT OF ARTIFICIAL INTELLIGENCE AND DATA SCIENCE R.M.K. College of Engineering and Technology, MISSILE MAN SCIENTIFIC AND RESEARCH PUBLICATIONS 2026 置信度 0.77 computer sciencecomputer and information sciencesmachine learningartificial intelligencecryptography and security
• Machine Learning for Antimicrobial Resistance Prediction
  Antimicrobial resistance threatens modern medicine by rendering antibiotics ineffective against bacterial pathogens, andmachine learning models that predict resistance phenotypes from bacterial genome sequences offer rapid alternatives toculture-based suscepti…
  datacite Jonas Garcia, Laura Hansen, Clara Petrov 2023 置信度 0.73 antimicrobial resistance; machine learning; AMR prediction; bacterial genomics; AMPI; resistance genes; whole-genome sequencing; MIC prediction; clinical microbiology; susceptibility testing; CARD; ResFinder
• Machine Learning for Antimicrobial Resistance Prediction
  Antimicrobial resistance threatens modern medicine by rendering antibiotics ineffective against bacterial pathogens, andmachine learning models that predict resistance phenotypes from bacterial genome sequences offer rapid alternatives toculture-based suscepti…
  datacite Jonas Garcia, Laura Hansen, Clara Petrov 2023 置信度 0.73 antimicrobial resistance; machine learning; AMR prediction; bacterial genomics; AMPI; resistance genes; whole-genome sequencing; MIC prediction; clinical microbiology; susceptibility testing; CARD; ResFinder
• Информационная модель прогнозирования тяжести заболевания
  Данная работа посвящена разработке улучшенной информационной модели прогнозирования тяжести внебольничной пневмонии у детей методами машинного обучения. Задачи, которые решались в ходе исследования: 1. Обзор предметной области: клинические особенности внебольн…
  datacite Зиссерман, Елена Дмитриевна 2026 置信度 0.70 внебольничная пневмониямашинное обучениелогистическая регрессияслучайный лесградиентный бустинг
• FluSight: Two-Stage k-mer Random Forest Framework for Influenza A Zoonotic Risk Prediction
  Description This release archives the exact version of the FluSight pipeline submitted to the Journal of Medical Virology. FluSight is a hierarchical machine learning framework designed for alignment-free prediction of Influenza A host adaptation and zoonotic …
  datacite Chauhan, Maitry, Gupta, Aryan, Karthik, Shivram, Sharma, Akshi 等 2026 置信度 0.77 medicineartificial intelligencecomputer sciencebiological sciences not elsewhere classifiedworkflow
• FluSight: Two-Stage k-mer Random Forest Framework for Influenza A Zoonotic Risk Prediction
  Description This release archives the exact version of the FluSight pipeline submitted to the Journal of Medical Virology. FluSight is a hierarchical machine learning framework designed for alignment-free prediction of Influenza A host adaptation and zoonotic …
  datacite Chauhan, Maitry, Gupta, Aryan, Karthik, Shivram, Sharma, Akshi 等 2026 置信度 0.77 medicineartificial intelligencecomputer sciencebiological sciences not elsewhere classifiedworkflow
• AI-Based Osteoporosis Detection Using Clinical Bone Densitometry Data and Deep Learning Techniques
  Osteoporosis is a progressive bone disease characterized by decreased bone mineral density (BMD) and an increased risk of fractures, especially among elderly individuals and postmenopausal women. Early detection is crucial to prevent severe complications and i…
  datacite IJISEA 2026 置信度 0.77 artificial intelligencemedicineconvolutional neural networkcomputer scienceworkflow
• AI-Based Osteoporosis Detection Using Clinical Bone Densitometry Data and Deep Learning Techniques
  Osteoporosis is a progressive bone disease characterized by decreased bone mineral density (BMD) and an increased risk of fractures, especially among elderly individuals and postmenopausal women. Early detection is crucial to prevent severe complications and i…
  datacite IJISEA 2026 置信度 0.77 artificial intelligencemedicineconvolutional neural networkcomputer scienceworkflow
• Explainable Transformer Models for Clinical Prediction Tasks on Structured Electronic Health Records
  Predictive models over structured electronic health records (EHRs) remain central to machine learning for healthcare, but few have jointly emphasized quantitative laboratory information and interpretability with respect to input medical events. We present BERT…
  datacite Du, Jun Ni, Adamek, Lukas, Kryukov, Maxim, Dormont, Flavio 等 2026 置信度 0.76 Machine Learning (cs.LG)FOS: Computer and information sciences
• Flow Matching Meets 3D Curvilinear Structure Segmentation in Medical Imaging
  Segmentation of curvilinear anatomical structures in 3D medical images remains challenging due to complex topology, severe class imbalance, weak contrast, and large variations in structure morphology. While deep learning approaches for 3D curvilinear segmentat…
  datacite Moctar, Sidi Mohamed Sid'El, Vitry, Nicolas, Bouvrais, Hélène 2026 置信度 0.77 Computer Vision and Pattern Recognition (cs.CV)Machine Learning (cs.LG)Quantitative Methods (q-bio.QM)FOS: Computer and information sciencesFOS: Biological sciences
• In a heartbeat: discovering complex cardiac motion signatures with machine learning
  Cardiac remodelling describes a range of adaptive responses to stress across physiological scales, governed by diverse molecular pathways. Traditional imaging-based assessments primarily rely on volumetric metrics, which serve as global indicators of function …
  datacite Schiratti, Pierre-Raphaël 2025 置信度 0.77 artificial intelligencecomputer sciencecomputer and information sciencescs.lgmedicine
• Clinical application of artificial intelligence to improve glaucoma care using imaging modalities
  Glaucoma, a leading cause of irreversible blindness, presents significant challenges for early diagnosis and timely intervention due to its asymptomatic nature and subtle clinical morphology. Early detection and intervention are critical for preventing the dis…
  datacite Abadh Chaurasia 2026 置信度 0.72
• Clinical application of artificial intelligence to improve glaucoma care using imaging modalities
  Glaucoma, a leading cause of irreversible blindness, presents significant challenges for early diagnosis and timely intervention due to its asymptomatic nature and subtle clinical morphology. Early detection and intervention are critical for preventing the dis…
  datacite Abadh Chaurasia 2026 置信度 0.72
• Martingale R-learner: Estimating Time-varying Heterogeneous Treatment Effects for Time-to-event Outcomes
  Biological research and clinical evidence suggest that treatment response may vary substantially along characteristics, such as comorbidities, genetic variants, environmental, or socio-economic factors. Future precision medicine requires accurate assessment of…
  datacite Hou, Jue, Qi, Yuchen, Xu, Ronghui 2026 置信度 0.76 Methodology (stat.ME)FOS: Computer and information sciences
• A Two-Stage Time-Aware Transformer for Short-Horizon AECOPD Risk Prediction
  Acute exacerbation of chronic obstructive pulmonary disease (AECOPD) can worsen rapidly, making timely prediction a clinical priority. Most existing machine learning approaches rely on episodically collected clinical variables, introducing delays that limit th…
  datacite Wang, Dongyang, Qu, Weihao, Zheng, Ling, Pan, Haowen 2026 置信度 0.76 Machine Learning (cs.LG)FOS: Computer and information sciences
• Operational Outcomes of Artificial Intelligence–Enabled Digital Interventions for Patient Flow and Capacity Management in Hospital Emergency Departments: A Scoping Review
  This scoping review aims to map the operational outcomes and organizational and implementation determinants reported following the prospective or routine implementation of artificial intelligence (AI)–enabled digital interventions in hospital emergency departm…
  datacite Gonzalo Alberto Peralta-Jiménez 2026 置信度 0.79 Health Information TechnologyOther Medicine and Health SciencesMedicine and Health SciencesHealth and Medical Administrationartificial intelligence
• Synthetic Turkish Clinical Event Dataset for Temporal Risk Prediction, Sequence Modeling, and NLP
  This dataset contains a synthetic Turkish clinical event dataset designed for temporal risk prediction, sequence modeling, and healthcare-related machine learning research. The dataset simulates longitudinal patient records, including visits, diagnoses, lab te…
  datacite Bayankulu, Senih 2026 置信度 0.79 synthetic-datahealthcareclinical-datatemporal-datasequence-modeling
• Synthetic Turkish Clinical Event Dataset for Temporal Risk Prediction, Sequence Modeling, and NLP
  This dataset contains a synthetic Turkish clinical event dataset designed for temporal risk prediction, sequence modeling, and healthcare-related machine learning research. The dataset simulates longitudinal patient records, including visits, diagnoses, lab te…
  datacite Bayankulu, Senih 2026 置信度 0.79 synthetic-datahealthcareclinical-datatemporal-datasequence-modeling
• Arabic Parkinson's Disease Speech Dataset
  This dataset contains audio recordings collected to investigate acoustic biomarkers and machine learning models for detecting Parkinson’s Disease (PD) in native Arabic speakers. Designed to support voice pathology detection, acoustic feature extraction, and cr…
  datacite Hassanat, Ahmad, Almahadin, Alaa O. 2026 置信度 0.76 Parkinson's Disease, Arabic Speech Dataset, Audio Processing, Acoustic Biomarkers, Machine Learning, Voice Analysis, Cross-Linguistic Validation
• Arabic Parkinson's Disease Speech Dataset
  This dataset contains audio recordings collected to investigate acoustic biomarkers and machine learning models for detecting Parkinson’s Disease (PD) in native Arabic speakers. Designed to support voice pathology detection, acoustic feature extraction, and cr…
  datacite Hassanat, Ahmad, Almahadin, Alaa O. 2026 置信度 0.76 Parkinson's Disease, Arabic Speech Dataset, Audio Processing, Acoustic Biomarkers, Machine Learning, Voice Analysis, Cross-Linguistic Validation
• Synthetic Dataset for Detecting the Relationship Between Psychological Illnesses and Criminal Tendency Patterns Using Machine Learning
  This record contains synthetic datasets generated for the study titled “Detecting the Relationship Between Psychological Illnesses and Criminal Tendencies Using Machine Learning.” The datasets were created for research and machine learning modeling purposes an…
  datacite Bilgin, Sümeyra, Vural, Mehmet Sait 2026 置信度 0.77 artificial intelligencecomputer sciencepsychologymachine learningcs.lg
• Synthetic Dataset for Detecting the Relationship Between Psychological Illnesses and Criminal Tendency Patterns Using Machine Learning
  This record contains synthetic datasets generated for the study titled “Detecting the Relationship Between Psychological Illnesses and Criminal Tendencies Using Machine Learning.” The datasets were created for research and machine learning modeling purposes an…
  datacite Bilgin, Sümeyra, Vural, Mehmet Sait 2026 置信度 0.77 artificial intelligencecomputer sciencepsychologymachine learningcs.lg
• Explainable Machine Learning and Deep Learning for Alzheimer's Disease Detection from Structural MRI and Clinical Data
  datacite Chennoufi, Ines, Chih, Chaima Malak 2026 置信度 0.62
• Explainable Machine Learning and Deep Learning for Alzheimer's Disease Detection from Structural MRI and Clinical Data
  datacite Chennoufi, Ines, Chih, Chaima Malak 2026 置信度 0.62
• HF-ETIOLOGY: Program Team Update Meeting (August 2026)
  This is a presentation from the August 2026 update to the NIH Program Team for the HF-ETIOLOGY Project.
  datacite Luo, Yuan, Cheng, Feixiong, Holmes, Kristi, Wang, Fei 2026 置信度 0.66 Behavioral Sciences/methodsBiological FactorsClinical MedicineData Collection/statistics & numerical dataData Curation/statistics & numerical data
• HF-ETIOLOGY: Program Team Update Meeting (August 2026)
  This is a presentation from the August 2026 update to the NIH Program Team for the HF-ETIOLOGY Project.
  datacite Luo, Yuan, Cheng, Feixiong, Holmes, Kristi, Wang, Fei 2026 置信度 0.66 Behavioral Sciences/methodsBiological FactorsClinical MedicineData Collection/statistics & numerical dataData Curation/statistics & numerical data
• Comprehensive Evaluation of Support Vector Machine Models Based on Kernels for Predicting Multiple Diseases
  In today's digital age, data is invaluable, and massive amounts of data have been produced in every field imaginable. Reports from the healthcare sector often contain details about patients' health. By having this clinical expertise, we are better able to dete…
  datacite G Swathika, K Venkata Ramaiah 2026 置信度 0.77 cs.lgmedicineartificial intelligencemachine learningconvolutional neural network
• Comprehensive Evaluation of Support Vector Machine Models Based on Kernels for Predicting Multiple Diseases
  In today's digital age, data is invaluable, and massive amounts of data have been produced in every field imaginable. Reports from the healthcare sector often contain details about patients' health. By having this clinical expertise, we are better able to dete…
  datacite G Swathika, K Venkata Ramaiah 2026 置信度 0.77 cs.lgmedicineartificial intelligencemachine learningconvolutional neural network
• What are the potential benefits and limitations of using machine learning algorithms to predict arrhythmogenic events in patients with long QT syndrome?
  Machine learning algorithms offer potential benefits in predicting arrhythmogenic events in long QT syndrome, though challenges around data quality, validation, and ethical issues present significant hurdles for clinical implementation.
  datacite Tripdatabase 2026 置信度 0.76 machine learningarrhythmogenic eventslong QT syndromepredictive algorithmscardiology
• What are the potential benefits and limitations of using machine learning algorithms to predict arrhythmogenic events in patients with long QT syndrome?
  Machine learning algorithms offer potential benefits in predicting arrhythmogenic events in long QT syndrome, though challenges around data quality, validation, and ethical issues present significant hurdles for clinical implementation.
  datacite Tripdatabase 2026 置信度 0.76 machine learningarrhythmogenic eventslong QT syndromepredictive algorithmscardiology
• Code for: GRAD: A Two-Stage Machine Learning Algorithm Resolves the Plasma p-Tau217 Diagnostic Gray Zone for Amyloid PET Prediction
  Two-stage diagnostic algorithm (Gatekeeper-Reflex for Alzheimer's Diagnostics) that resolves diagnostic uncertainty in plasma p-tau217 testing by combining a univariate logistic regression screen with a multi-marker random forest classifier for gray zone cases…
  datacite Parankusham, Harthik, Vanderlip, Casey, Birkenbihl, Colin Jan, Krishna, Eashwar 等 2026 置信度 0.76 Alzheimer's diseaseplasma biomarkersp-tau217amyloid PETmachine learning
• Data and Code for Machine Learning Based Reference Assisted Signal Recovery Under Anatomical Domain Shift in Simulated Radiofrequency Fracture Sensing
  Version 1.1.0 of the public data-and-code release supporting the article “Machine Learning Based Reference Assisted Signal Recovery Under Anatomical Domain Shift in Simulated Radiofrequency Fracture Sensing”. The release contains the canonical processed featur…
  datacite AlDelemy, Ahmad, Al Dulaimi, Ali, Abd-Alhameed, Raed 2026 置信度 0.79 radiofrequency fracture sensingdeep learningmachine learninganatomical domain shiftdomain generalisation
• Data and Code for Machine Learning Based Reference Assisted Signal Recovery Under Anatomical Domain Shift in Simulated Radiofrequency Fracture Sensing
  Version 1.1.0 of the public data-and-code release supporting the article “Machine Learning Based Reference Assisted Signal Recovery Under Anatomical Domain Shift in Simulated Radiofrequency Fracture Sensing”. The release contains the canonical processed featur…
  datacite AlDelemy, Ahmad, Al Dulaimi, Ali, Abd-Alhameed, Raed 2026 置信度 0.79 radiofrequency fracture sensingdeep learningmachine learninganatomical domain shiftdomain generalisation
• A Labeled Accelerometry Dataset of Steps and Postures Across Diverse Mobility and Frailty Levels in Older Adults in a Hospital Setting
  The Mobility in Geriatrics (Mobi-G) dataset is an open-access dataset designed to support the development, validation, and benchmarking of machine learning algorithms for posture classification and step counting in older adults. The dataset includes ankle-worn…
  datacite Lanoie, Annik, Cheung, Weng-Jy Cheung, Nguyen, Quoc Dinh 2026 置信度 0.79 Medicine, Health and Life SciencesSensorsAccelerometryGeriatricsMobility
• ARTIFICIAL INTELLIGENCE AND PRECISION MEDICINE IN PARKINSON'S DISEASE: EMERGING DIAGNOSTIC AND THERAPEUTIC APPROACHES
  Background: Parkinson's disease (PD) is heterogeneous, both clinically, genetically and neuropathologically, which presents ongoing challenges for conventional syndromic clinical diagnostic criteria and uniform treatments. Recent advances in biofluid biomarker…
  datacite Payal Patidar, Soma Sekhar Pulamarasetti*, Omkar Rai, Karan Gupta¹, Shivlal Yadav 2026 置信度 0.77 medicinecomputer scienceartificial intelligencedata sciencedisease