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• Machine learning-based prediction of E. coli infection in hospitalized patients using a no-code analytical framework.
  Hospital-acquired infections (HAIs) remain a major global concern, contributing significantly to increased morbidity, mortality, and healthcare costs. Among the causative pathogens, Escherichia coli (E. coli) is one of the most frequently isolated microorganis…
  europepmc 2026 置信度 0.94 medicineartificial intelligencecomputer scienceintensive care medicineinternal medicine
• Development and validation of a machine learning-based risk prediction model for PICC-associated bloodstream infections in preterm infants: a retrospective multicenter study.
  Objective To develop and validate a machine learning-based model for predicting the risk of peripherally inserted central catheter (PICC)-associated bloodstream infection (CRBSI) in preterm infants. Methods This retrospective multicenter study included 151 pre…
  europepmc 2026 置信度 0.94 medicinebiotechnologybiological sciences not elsewhere classifiedcancerartificial intelligence
• Development and temporal validation of a prediction model for cognitive impairment in older adults with hearing loss based on the population health risk management framework.
  Background Older adults with hearing loss are at increased risk of cognitive impairment, yet tailored risk stratification tools remain limited. Methods In this cross-sectional study, 524 adults aged ≥60 years with hearing loss were enrolled between June 2023 a…
  europepmc 2026 置信度 0.94 medicinepsychologybiological sciences not elsewhere classifiedscience policyinternal medicine
• Machine learning models predicting extubation success in mechanically ventilated patients: a systematic review and meta-analysis.
  Background Optimal timing of extubation in mechanically ventilated patients remains a major challenge in intensive care. Machine learning (ML) models have been increasingly proposed to support clinical decision-making, yet their predictive performance and read…
  europepmc 2026 置信度 0.94 medicineartificial intelligencemedlinecomputer sciencebiological sciences not elsewhere classified
• Machine learning prediction of post-traumatic osteoarthritis based on three-dimensional printing-derived joint congruence biomechanics in ankle fractures.
  Objective Post-traumatic osteoarthritis (PTOA) develops in 20-40% of patients following ankle fracture fixation despite anatomic reduction. This study aimed to develop a machine learning model incorporating three-dimensional (3D) printing-derived joint congrue…
  europepmc 2026 置信度 0.94 medicineinternal medicinescience policyphysical medicine and rehabilitationbiological sciences not elsewhere classified
• Utilizing Serum Fluorescence Spectra and Machine Learning Algorithms for Efficient Diagnosis of Sheep Brucellosis.
  In sheep, the infectious disease brucellosis is caused by Brucella melitensis. Traditional serological techniques for detecting Brucella in sheep are slow and not very accurate, necessitating a faster and more precise screening method. This study seeks to asse…
  europepmc 2026 置信度 0.94 biological sciences not elsewhere classifiedmicrobiologybrain-computer interfaceexoplanetidentification
• Mental Health Risk Detection From Social Media Text Data: A Scoping Review of the Machine Learning Research Landscape.
  Machine learning approaches have been increasingly applied to social media text data for mental health risk detection. However, existing studies vary widely in target outcomes, data sources, labeling strategies, and evaluation practices, and a structured overv…
  europepmc 2026 置信度 0.94 artificial intelligencemedicinemental healthmedlinepsychological intervention
• Development and internal validation of an interpretable machine learning model using first-24-h postpartum nursing variables to predict delayed lactogenesis II after cesarean delivery.
  Background Delayed lactogenesis II is a common early postpartum breastfeeding problem after cesarean delivery and may interfere with the establishment of exclusive breastfeeding. Although demographic and obstetric risk factors have been widely studied, the pre…
  europepmc 2026 置信度 0.94 medicineartificial intelligencemedlineinternal medicinescience policy
• A combined model based on clinical, radiomics, and deep transfer learning features for differentiating endometrial hyperplasia with polyps from endometrial cancer.
  Objective This study aimed to develop an ultrasound-based deep learning radiomics nomogram for differentiating endometrial hyperplasia with polyps from endometrial cancer in endometrial lesions and to explore its clinical diagnostic efficacy. Methods We retros…
  europepmc 2026 置信度 0.94 medicineartificial intelligenceinternal medicinemedical physicsmedline
• Predicting Critical Outcomes in Suspected Cardiopulmonary Emergencies Using Dispatch Narratives: Temporal Validation Study.
  Background Early risk stratification in emergency medical services (EMS) is essential for patients presenting with acute cardiopulmonary symptoms, yet prehospital decision-making at the dispatch stage is often based on limited structured information. Free-text…
  europepmc 2026 置信度 0.94 medicinecomputer scienceinternal medicineartificial intelligencebiological sciences not elsewhere classified
• Explainable XGBoost model and nomogram for risk factor identification and risk prediction in cerebral small vessel disease: a machine learning-based retrospective cohort study.
  Background Cerebral small vessel disease (CSVD) is a common, clinically significant vascular disorder that frequently leads to cognitive impairment, dementia, and poor overall prognosis. Owing to its complex hemodynamic characteristics and multifactorial patho…
  europepmc 2026 置信度 0.94 medicineartificial intelligenceinternal medicinebiological sciences not elsewhere classifiedintensive care medicine
• Integrating physics guidance into deep learning for cine cardiovascular segmentation.
  Cine cardiovascular magnetic resonance (CMR) provides dynamic sequences for quantifying clinically important indices such as ventricular volumes and ejection fraction. A fast and accurate deep segmentation model is therefore valuable for timely analysis, reduc…
  pubmed Tran-Nguyen MA, Luong QK, Kha MB, Dang TL 2026 Aug 置信度 0.96 computer and information sciencescs.lgcs.aicomputer sciencerobotics
• Learning generalizable representations across Heterogeneous Acquisition Environments for Breast Ultrasound Diagnosis.
  Ultrasound image classification remains challenging in clinical practice, given substantial variations in image appearance across devices, acquisition protocols, and operator habits, often unrelated to underlying pathology and associated with inconsistent mode…
  pubmed Wang H, Zhang S, Kong W, Shao W 等 2026 Aug 置信度 0.96 computer and information sciencescs.lgcs.aics.cvartificial intelligence
• Fusion of ERP and fNIRS signals for classification of internet gaming disorder in an attention-modulating dot-probe task.
  Internet gaming disorder (IGD) has emerged as a significant behavioral addiction and public health concern. However, its underlying neurobiological mechanisms remain unclear. This study aimed to develop a machine learning approach to evaluate IGD based on mult…
  pubmed Altınkaynak M, Batbat T, Yeşilbaş D, Güven A 等 2026 Oct 置信度 0.93 mental healthmedicinediseaserehabilitationpsychological intervention
• V(2)-Former: Towards volumetric framework for instance-level segmentation and prediction of fetal ventriculomegaly in anisotropic MRI.
  Accurate identification and assessment of fetal ventriculomegaly (VM) is crucial for prenatal care. However, conventional diagnosis relies on manual 2D slice-based measurements, which may overlook 3D morphological cues. Existing deep learning approaches typica…
  pubmed Zhang Z, Zhang L, Huang W, Wang Y 等 2026 Sep 置信度 0.96 artificial intelligencemedicinecs.aicomputer and information sciencescs.cv
• Spatial phenotyping of epicardial adipose tissue from cardiac MRI.
  Epicardial adipose tissue (EAT) is increasingly recognized as an important contributor to cardiovascular disease (CVD), but its spatial distribution across the heart remains insufficiently characterized due to limitations in existing segmentation and analysis …
  pubmed Feng F, Long T, Hasaballa AI, Sun X 等 2026 Sep 置信度 0.96 medicinebiotechnologyscience policybiological sciences not elsewhere classifiedcell biology
• Machine learning and deep learning for ankle fracture detection in radiographs: A systematic review with narrative synthesis on diagnostic performance and future clinical integration.
  Ankle fractures are a prevalent orthopedic injury with X-rays being the primary diagnostic tool. Errors in radiological interpretation leads to missed fractures and delayed diagnosis. This systematic review with narrative synthesis aims to map the current land…
  pubmed Mangwani J, Jithin SP, Akram N, Ravi L 等 2026 Sep 置信度 0.96 medicine and health sciencescs.lgmedlineconvolutional neural networkmedical physics
• Can AI-based chatbots enhance patient education and support nursing practice for hip replacement patients? A scoping review.
  Artificial intelligence (AI), particularly machine learning and large language models (LLMs), has seen rapid advancements and widespread adoption over the past decade, transforming many fields, including healthcare. ChatGPT is one of the prominent chatbot inte…
  pubmed Kaur J, Adedoyin F, Budka M, Wainwright TW 2026 Aug 置信度 0.96 computer sciencegenerative grammarartificial intelligencepsychologycs.lg
• Multiturn Large Language Model-Based Conversational Agents for Patients With Cancer and Caregivers: Scoping Review.
  Large language model (LLM)-based conversational agents are increasingly used in health care, yet their capacity to support genuine multiturn dialogue remains underexplored. In oncology, where patients and caregivers experience complex informational and emotion…
  pubmed Jeong Y, Cha H, Suh EE 2026 Jul 21 置信度 0.96 medicinepsychological interventionscience policymental healthmedicine and health sciences
• Prediction of factors contributing to Pain Intensity among low back pain patients: A comparative machine learning frameworks (Random Forest versus XGBoost).
  Predicting pain intensity in patients with low back pain (LBP) remains a complex task due to the biopsychosocial nature of pain. Pain intensity is shaped by multifaceted interactions among demographic, lifestyle, and clinical factors.
  pubmed Algamdi MM, Alghamdi AH 2026 置信度 0.93 intensive care medicineinternal medicinerehabilitationphysical medicine and rehabilitationdisease
• Feature integration of [18F]FDG PET brain imaging using deep learning for sensitive cognitive decline detection.
  Distinguishing individuals with cognitive decline (CD), including early Alzheimer's disease, from cognitively normal (CN) individuals is essential for improving diagnostic accuracy and enabling timely intervention. Positron emission tomography (PET) captures m…
  pubmed Lee Y, Kim S, Kang Y, Alzheimer’s Disease Neuroimaging Initiative 2026 置信度 0.96 medicineneuroscienceneuroimagingdiseasehealth care
• Brain aging patterns among nine neurological disorders: A case-control study.
  The difference between neuroimaging-predicted brain age and chronological age, the predicted age difference (PAD), has been studied as a potential biomarker reflecting individual brain health. Although previous large-scale studies have shown that brain age dev…
  pubmed Liang C, Pearlson G, Bustillo J, Kochunov P 等 2026 Jul 置信度 0.96 neuroimagingpsychologyneurosciencecognitioncognitive psychology
• Post-COVID-19 Condition Diagnosis among Older People: Findings from Swedish National Register Data.
  Post-COVID-19 condition (PCC) denotes the persistence of symptoms following Severe Acute Respiratory Syndrome Coronavirus 2 infection. PCC poses a large disease burden worldwide. We aimed to explore the epidemiological characteristics of clinically diagnosed P…
  pubmed Zhang Z, Hoang MT, Wastesson JW, Johnell K 2026 Jul 21 置信度 0.93 medicineinternal medicinediseaseintensive care medicinesocial and behavioral sciences
• The FACT-Score: Development and Temporal Validation of a Clinical Risk Stratification Tool for 30-Day Complications After Operative Facial Fracture Repair.
  No validated, procedure-specific tool exists for predicting 30-day complications after operative facial fracture repair. This study aimed to develop and temporally validate a clinical risk stratification tool for 30-day complications after operative facial fra…
  pubmed Catic A, Karamitros G, Lineaweaver WC, Lamaris GA 等 2026 Jul 20 置信度 0.89 internal medicineintensive care medicinebioinformaticsmedical physicsdisease
• Individual-Specific Functional Connectivity-Based State Classification and Prognosis Prediction for Disorders of Consciousness.
  Accurate prognosis and treatment targeting for disorders of consciousness (DOC) remain challenging due to profound neurobiological heterogeneity. Current approaches to DOC state classification and prognostic prediction, which rely on resting-state functional m…
  pubmed Wan Z, Chen G, Li H, Bai Y 2026 置信度 0.96 computer and information sciencesartificial intelligencecs.lgcs.aibrain-computer interface
• Integrated bioinformatics and experimental analysis identify apoptosis- and pyroptosis-related hub genes as candidate diagnostic biomarkers in Alzheimer's disease.
  Apoptosis and pyroptosis-mediated neuronal death represent major pathogenic mechanisms underlying Alzheimer's disease (AD). Given the potential crosstalk between these two forms of cell death, investigation of a single death pathway may be insufficient to iden…
  pubmed Cai Y, Chen Y, Huang G, Ren M 等 2026 Jul 21 置信度 0.96 medicinebiologybiological sciences not elsewhere classifiedgeneticspharmacology
• Machine learning algorithms for predicting arrhythmic events in Hypertrophic Cardiomyopathy: limited enhancement beyond late gadolinium enhancement.
  We aimed to develop and assess the performance of a Machine learning (ML) model integrating common clinical features to predict arrhythmic events in patients with Hypertrophic Cardiomyopathy (HCM). Post-hoc analysis of an international multicenter registry of …
  pubmed Certo Pereira J, Amador R, Vieira A, Almeida Carvalho R 等 2026 Jul 21 置信度 0.96 medicineinternal medicinemedlinediseasebiotechnology
• Moving on in hydrocephalus imaging: from 2D to 3D biomarkers.
  Linear two-dimensional indices such as the Evans index, callosal angle, and fronto-occipital horn ratio remain the clinical standard for hydrocephalus assessment, yet are limited by measurement variability, insensitivity to spatial CSF redistribution, and redu…
  pubmed Da Mutten R, Turczynski Holmgren R, Edström E, Elmi-Terander A 等 2026 Jul 21 置信度 0.96 medicinemedical physicsintensive care medicinescience policydisease
• Predicting the absence of World Health Organization fungal priority pathogens in agricultural soils using machine learning and ITS metabarcoding.
  Environmental fungal pathogens relevant to human and animal health pose significant risks, particularly in regions with intensive farming and climate variability. Several taxa detected in Thailand's clinical and environmental samples, such as Candida tropicali…
  pubmed Ibrahim SNMM, Jaikla C, Pombubpa N 2026 Jul 21 置信度 0.96 biologymedicineecologybiological sciencesbiotechnology
• Artificial intelligence for pediatric neuroimaging.
  Artificial intelligence (AI) is revolutionizing health care, particularly in radiology for which large retrospective electronic datasets are naturally suited to training large machine and deep learning models. To date, the vast majority of United States Food a…
  pubmed Ho ML 2026 Jul 21 置信度 0.96 medicinecomputer scienceartificial intelligencemedical physicsdata science
• AI-assisted TURP slide review: a multi-reader study of efficiency, diagnostic performance, and human-AI error patterns.
  Transurethral resection of the prostate (TURP) specimens represent a low-prevalence, high-volume diagnostic task in which pathologists must identify rare malignant foci within large amounts of predominantly benign tissue. Although artificial intelligence (AI) …
  pubmed Pascarella CB, Giobbe M, Maffei E, Ruotolo R 等 2026 Jul 21 置信度 0.96 medicineartificial intelligencepsychologycs.aibrain-computer interface
• Novel Musculoskeletal Hypotheses in the Armed Services Trauma and Rehabilitation Outcome (ADVANCE) Cohort: Development and Application of Sparse Group Factor Analysis Methodology.
  Musculoskeletal conditions are a leading global cause of disability, yet the factors influencing long-term musculoskeletal health, particularly following trauma, remain incompletely understood. Machine learning could be applied to identify previously unknown p…
  pubmed Watson FCE, Ferreira FS, Kadirvelu B, Bennett AN 等 2026 Jul 21 置信度 0.93 intensive care medicineinterpretabilitydiseasepsychological interventionmicrobiology
• COLOSSUS-AI: A Pilot Study on Artificial Intelligence Driven Prediction of Postoperative Outcomes in Colorectal Surgery.
  Background: Postoperative complications remain a major source of morbidity after colorectal surgery and are associated with prolonged hospitalization, reintervention, intensive care unit admission, and increased mortality. Early identification of high-risk pat…
  pubmed Botoncea M, Cosma CD, Nicolescu CL, Butiurca VO 等 2026 Jun 置信度 0.96 medicineartificial intelligenceinternal medicinebiotechnologymachine learning
• A Locally Executable AI System for Improving Preoperative Patient Communication: Multidomain Clinical Evaluation.
  Patients undergoing invasive procedures frequently experience anxiety and often have unanswered questions regarding the procedure. Although large language models show considerable promise for supporting patient communication in many cases, their deployment in …
  pubmed Sato M, Nagata S, Ohnuma M, Takahashi H 等 2026 Jul 21 置信度 0.96 health careintensive care medicinemedical educationlarge language modelsmental health
• Medical AI Agents for Clinical Decision Support: Viewpoint Using the Planning, Action, Reflection, and Memory (PARM) Analytical Lens.
  Medical AI agents are emerging as a new generation of clinical decision support systems, moving beyond static prediction toward multistep, workflow-oriented assistance. This Viewpoint argues that agentic architectures incorporating planning, action, reflection…
  pubmed Dinc R, Ardic N 2026 Jul 21 置信度 0.96 computer scienceartificial intelligenceworkflowcs.aisoftware deployment
• Stress CMR ischemic burden and long-term mortality in left ventricular systolic dysfunction: a multicenter registry study.
  Stress perfusion cardiovascular magnetic resonance (CMR) integrates assessment of myocardial ischemia, scar, and function. Its incremental prognostic value in patients with left ventricular (LV) systolic dysfunction remains uncertain.
  pubmed Pfeffer A, Garot J, Duhamel S, Garot P 等 2026 Jul 21 置信度 0.83 internal medicinemedicineintensive care medicinediseasescience policy
• Structured Clinical Input-Guided Large Language Model Workflow for Acute Ischemic Stroke Discharge Education: A Multicenter Feasibility Study.
  Large language models (LLMs) may support patient education, but their clinical use remains challenging. We aimed to evaluate the preliminary feasibility of a structured clinical input-guided LLM workflow for generating discharge education drafts for patients w…
  pubmed Yin J, Wang W, Wu L, Li Z 等 2026 Sep 置信度 0.93 medicineworkflowmedical educationmedlinelarge language models
• Artificial Intelligence-Based Analysis of Coronary Atherosclerotic Plaque on Intravascular Ultrasound: A Systematic Review and Meta-Analysis.
  Coronary atherosclerotic plaque detection is essential for the diagnosis and management of coronary artery disease. Although intravascular ultrasound (IVUS) enables detailed plaque assessment, its clinical use is limited by time-consuming interpretation and ob…
  pubmed Eini P, Serpoush H, Rezayee M, Kassulke M 2026 Jul 置信度 0.96 medicinemedical physicsinternal medicineintensive care medicinedisease
• Automated Differentiation of Oral Red-White Lesions: An Interpretable Deep Learning Approach Combining Ensemble Architectures and Saliency Maps.
  Oral Potentially Malignant Disorders (OPMDs), including Leukoplakia and Erythroplakia, carry significant risks of malignant transformation. Early differentiation from confounding inflammatory conditions like Oral Lichen Planus (OLP) and Candidiasis is critical…
  pubmed Koochaki M, Mousavie A, Basirat M, Hendi A 等 2026 Aug 置信度 0.91 deep learningscience policyconvolutional neural networkbiotechnologycomputer vision and pattern recognition
• Development of a Predictive Model for Transfusion-Related Acute Lung Injury Based on Neutrophil Extracellular Traps (NETs).
  Patients receiving massive transfusion after acute hemorrhage are at risk for transfusion-related acute lung injury (TRALI), a severe complication. Neutrophil extracellular traps (NETs) play a key role in acute lung injury. This study aimed to explore the link…
  pubmed Wang Q, Li Z, Shao J, Qiang X 等 2026 置信度 0.93 medicineintensive care medicineinternal medicinerehabilitationcancer
• Scalable, context-sensitive psychiatric assessment with large language models and brief diaries.
  Accurate psychiatric assessment requires understanding a person's unique experience within their psychosocial context. Clinical interviews have been the gold standard for assessment as the only methods capable of this complex task, but they are time and resour…
  pubmed Ringwald WR, Taxali A, Angstadt M, Vize CE 等 2026 Jul 21 置信度 0.96 cs.clcs.ainatural language processingpsychologyinternal medicine
• Tailored injectable nanocomposite hydrogels for high-performance biomedical applications.
  Conventional hydrogel systems for biomedical applications face critical limitations in mechanical robustness, therapeutic functionality, and responsiveness to physiological stimuli, hindering their translation to precision medicine. The rational integration of…
  pubmed Rathee G, Singh NK, Kohli S, Deshmukh K 等 2026 Aug 25 置信度 0.96 medicinecomputer scienceartificial intelligencedata scienceengineering
• FGSGT-DDI: An LLM-Enhanced Functional Group Semantic Graph Transformer for Drug-Drug Interaction Prediction.
  Drug-drug interaction (DDI) prediction is of great importance for drug discovery and safe clinical medication use. Existing methods mainly rely on molecular graph structure modeling but make insufficient use of functional group semantic information, which limi…
  pubmed Li K, Qiao J, Yang Y, Zhao H 等 2026 Aug 10 置信度 0.96 cs.lgcomputer and information sciencescs.aics.cvcomputer science
• CT-Based Radiomic Features Predict Cervical Lymph Node Metastasis in Dogs With Oral Malignancy: A Machine Learning Study Using Leave-One-Patient-Out Cross-Validation.
  Accurate preoperative identification of cervical lymph node (LN) metastasis is essential for staging and treatment planning in dogs with oral malignancy, yet conventional imaging offers limited diagnostic sensitivity. This retrospective study evaluated whether…
  pubmed Pinard CJ, Lagree A, Appleby R, Oblak M 等 2026 Jul 20 置信度 0.96 medicineartificial intelligencescience policycancerbiological sciences not elsewhere classified
• DHCA-Net: A Novel Dual-Stream Hierarchical Channel Attention Network for Explainable Autism Spectrum Disorder Detection From Facial Images.
  Autism spectrum disorder (ASD) consists of a spectrum of neurodevelopmental conditions characterized by complex behavioural traits and subtle, atypical facial morphologies. Analysing these facial biomarkers provides a promising, non-invasive avenue for objecti…
  pubmed Singh DP, Banerjee T, C ADD, Shukla SM 等 2026 Aug 置信度 0.96 computer scienceartificial intelligencecs.aicomputer and information sciencescs.cv
• Machine learning models for injury risk prediction in football players: A systematic review of predictors, performance, practical applications, and limitations.
  ObjectiveFootball is associated with a high incidence of musculoskeletal injuries because of its dynamic, high-intensity, and contact nature. Machine learning methods offer the potential to capture nonlinear relationships among diverse risk factors. This syste…
  pubmed Aslani M, Zarei M, Yaghoubitajani Z, Malekahmadi A 2026 Jul 置信度 0.96 medicinemedlinesystematic reviewcomputer scienceartificial intelligence
• Nurse-Led Identification of Financial Toxicity in Stroke Patients Using Machine Learning: Development and Validation of an Associational Prediction Model.
  To develop and validate a machine learning-based associational prediction model for nurse-led identification of financial toxicity (FT) among stroke patients.
  pubmed Song Y, Xing Y, Zong C, Liu H 等 2026 置信度 0.93 stat.mlinternal medicineintensive care medicinephysical medicine and rehabilitationnatural language processing
• Engineering selective amyloid precursor protein inhibitors by machine learning and deep mutational scanning.
  Deep mutational scanning (DMS) has proven effective for mapping protein-protein interactions (PPIs), but it cannot provide complete coverage of the mutation landscape, particularly for multi-mutant variants. To address this limitation, we trained machine-learn…
  pubmed Meiri R, Reuveni O, Levi M, Radisky ES 等 2026 Aug 置信度 0.96 medicinecomputational biologybiologycell biologydrug discovery
• Interpretable machine learning for cardiovascular disease risk prediction in cancer survivors: development and internal validation.
  Cardiovascular disease (CVD) is a major concern among cancer survivors. However, the intersection of cancer and CVD has only recently gained broader attention, and substantial evidence gaps remain. This study aimed to identify risk factors associated with inci…
  pubmed Zhang G, Zhang X, Jia C, Zhou H 等 2026 Jul 20 置信度 0.93 medicinediseaseinternal medicinecancerintensive care medicine
• Association of preoperative monocyte level with postoperative delirium in patients receiving cardiac surgery under propofol-based anesthesia: a retrospective study.
  Postoperative delirium is a common complication after cardiac surgery, and perioperative inflammation may contribute to its development. However, the association between preoperative blood indicators and postoperative delirium in patients receiving propofol-ba…
  pubmed Wen X, Shan J, Deng S, Ye G 等 2026 Jul 20 置信度 0.83 medicineinternal medicinecell biologyintensive care medicinemedical physics
• Reducing overconfident errors in clinical prediction models.
  Machine Learning (ML) models are increasingly being used in clinical workflows. Evaluation of these models tends to focus on global performance metrics, which can obscure error patterns and lead to bias in clinical decision making. Here, we propose Proximal Er…
  pubmed Bayly H, Tripodis Y, Lenio S, Patil P 等 2026 Jul 20 置信度 0.96 cs.lgmedicinecs.aimachine learningartificial intelligence
• Development and temporal validation of a machine-learning based risk prediction model for depression in older adults with chewing difficulty: evidence from the KNHANES.
  Depression in older adults is a multifactorial condition influenced by demographic, behavioral, and health-related factors. Oral functional problems, such as chewing difficulty, have received relatively limited attention despite potential relevance to mental h…
  pubmed Lee YS, Song D, Chang D, Youn BY 2026 置信度 0.96 medicinepsychological interventionpsychologymental healthmedline
• Beyond visual inspection: can a multimodal machine learning model improve the preoperative differentiation of endometrial polyps from non-polypoid endometrial lesions?
  To develop a multimodal machine learning model that integrates clinical data and ultrasound features to improve the non‑invasive preoperative differentiation between endometrial polyps (EMPs) and non‑polypoid endometrial lesions (including polypo…
  pubmed Ma D, Ye Z, Wang C, Lin H 等 2026 Jul 20 置信度 0.93 interpretabilitybig dataq-bio.gnconvolutional neural networkq-bio.mn
• AI-assisted decision support for sickle cell disease severity stratification using routine blood tests: a systematic review and meta-analysis.
  Stratifying sickle cell disease (SCD) severity remains challenging, particularly in resource-limited settings. Artificial intelligence (AI) models using routine complete blood count (CBC) parameters have been proposed as accessible tools for risk stratificatio…
  pubmed Ali NT, H Mehdi MA, Abdullah RS, Ali GS 等 2026 Jul 20 置信度 0.93 medical physicsmedical educationmedicineworkflowhealth care
• Screening of shared molecular markers between cervical cancer and major depressive disorder and the mechanism of CRAT/CLIC4 regulating EMT in cervical cancer cells.
  Cervical cancer (CC) ranks among the most prevalent malignant neoplasms affecting women worldwide. Tumor recurrence, distant metastases, and chemotherapy resistance significantly hinder long-term clinical survival and therapeutic outcomes. Clinical studies ind…
  pubmed Zhang HH, Liu M, Chen YN, Zhang MR 等 2026 Jul 20 置信度 0.91 medicinepharmacologydiseaseinternal medicineneuroscience
• Explainable machine learning model for early prediction of ICU death in chronic heart failure with pulmonary infection.
  To develop and validate a machine learning model for predicting ICU mortality in CHF patients with pulmonary infection.
  pubmed Zhai Y, Wei B, Lan D, Lv S 等 2026 Jul 20 置信度 0.84
• Mitochondria-localized protein-encoding genes and programmed cell death-related genes reveal potential molecular perturbations underlying spontaneous preterm birth.
  Multiple programmed cell death (PCD) modalities, including apoptosis, autophagy, and ferroptosis, are closely implicated in spontaneous preterm birth (SPTB). Mitochondria serve as central regulators of various PCD pathways, playing a critical role in cellular …
  pubmed Zuo L, Huai Q, Zhang M, Liu X 等 2026 Jul 20 置信度 0.86 pharmacologybiochemistrymicrobiologybiological sciences not elsewhere classifiedbiological sciences
• Advanced prediction of cardiovascular-kidney-metabolic syndrome using eight machine learning models and 24 composite indices.
  This study aimed to construct and validate a machine learning classifier for cross-sectionally stratifying existing cardiovascular-kidney-metabolic (CKM) syndrome stages using routine composite inflammatory, metabolic and anthropometric indices, and to interpr…
  pubmed Li M, Xiang J, Xiao F, Wang Q 等 2026 Jul 21 置信度 0.93 interpretabilitymathematics educationsustainabilitydrug discoverymedical education
• Exploratory clinical-CT machine learning characterization of CK7 expression in clear cell renal cell carcinoma.
  Cytokeratin 7 (CK7) expression in clear cell renal cell carcinoma (ccRCC) may reflect tumor phenotype and biological heterogeneity, but its clinical role remains exploratory. This study aimed to investigate associations between preoperatively available clinica…
  pubmed Lin Q, Miao G, Jia X, Zhang Y 等 2026 Jul 20 置信度 0.93 microbiologycancermedical physicsbiochemistrydisease
• Machine learning-based prediction of sepsis-induced myocardial injury: external validation and SHAP interpretation.
  Sepsis-induced myocardial injury (SIMI) is a common complication in sepsis patients with poor prognosis. Consequently, its early accurate prediction is crucial for optimizing clinical management.
  pubmed Li B, Pi S, Xu M, Mu H 等 2026 置信度 0.93 intensive care medicinemedicineinternal medicinemedical physicsdisease
• Integrated proteomics and machine learning for identifying candidate serum biomarkers in acute myocardial infarction-complicated cardiogenic shock: a prospective exploratory study.
  Cardiogenic shock secondary to acute myocardial infarction (AMI-CS) prohibitively impacts survival. This prospective study aimed to discover and internally verify candidate serum protein biomarkers and evaluate their potential prognostic value for 30-day morta…
  pubmed Wang X, Xiao QF, Huang FY, Wang S 等 2026 Jul 20 置信度 0.93 internal medicinemedicineintensive care medicinepsychological interventiondisease
• Integrating remote testing and machine learning to identify markers of cerebellar ataxia at home.
  In-person assessments face accessibility, scalability, and geographic diversity challenges, especially for rare diseases. Additionally, Cerebellar Ataxia (CA) non-motor symptoms(NMS) are often overlooked. We aimed to address these gaps by leveraging the Intern…
  pubmed Ponger P, De Picciotto Y, Maisel D, Liandres H 等 2026 Jul 20 置信度 0.93 resilienceinteroperabilitytransparencymanufacturing engineeringautomation
• Bioinformatics, Machine Learning and Functional Validation Reveal Mitophagy-Related FABP5 and HMOX1 as Diagnostic and Therapeutic Targets in Polycystic Ovary Syndrome.
  Polycystic Ovary Syndrome (PCOS) is a heterogeneous endocrine-metabolic disorder characterized by ovulatory dysfunction, hyperandrogenism, and insulin resistance, in which mitochondrial dysfunction has been increasingly implicated. Mitochondria regulate energy…
  pubmed Lian A, Li Y, He W, Luo X 等 2026 Jul 20 置信度 0.96 biologycomputational biologygeneticscell biologypharmacology
• Development and Evaluation of an Adaptive Penguin-Improved LSTM Model Integrating Natural Language Processing for Early Prediction of Pregnancy Syndrome Risks.
  Early prediction of pregnancy syndromes such as preeclampsia, gestational diabetes mellitus (GDM), and preterm birth is critical for improving maternal and fetal outcomes. Traditional risk assessment tools rely primarily on structured clinical data and often f…
  pubmed Wu Y 2026 Jul 置信度 0.93 medicineinternal medicinediseaselarge language modelsrisk analysis
• Pharmacokinetic Modeling of Hepatospecific MRI Contrast Agent Flux in Large Animal Models by Dynamic Contrast-Enhanced MRI.
  Evaluate the feasibility of using dogs and a pig as translational models for assessing hepatic flux of hepatospecific gadolinium-based contrast agents using dynamic contrast-enhanced MRI (DCE-MRI).
  pubmed Latourette MT, Hix JML, Huang J, Mallett CL 等 2026 Jul 20 置信度 0.83 benchmarkcs.macomputer vision and pattern recognitionlarge language modelscs.dc
• Identification of Microbiome Associations with Tacrolimus Pharmacokinetics in Adult Hematopoietic Cell Transplantation Using Population Pharmacokinetic and Machine Learning.
  Tacrolimus (TAC) is known for its high pharmacokinetic variability which cannot be fully explained by pharmacogenomic (PGx) and clinical variables. We identified gut microbiome associated with TAC pharmacokinetic variability in allogeneic hematopoietic cell tr…
  pubmed Mohamed ME, Cheng S, Staley C, Rashidi A 等 2026 Jul 20 置信度 0.93 intensive care medicinegeneticsdiseasebioinformaticsmicrobiology
• An Interpretable Machine Learning Model for Predicting the Presence of Talaromycosis in HIV Patients Lacking Skin Lesions.
  The existing predictive models for talaromycosis in people living with HIV without skin lesions are limited by established risk factors and traditional statistical approaches. This study aims to develop an interpretable machine learning(ML) model for predictin…
  pubmed Hu J, He W, Tian Q, Lu Y 等 2026 Jul 21 置信度 0.93 medicineinternal medicinediseaseinterpretabilityintensive care medicine
• A comprehensive evaluation of seven osteoporosis screening tools.
  This review evaluates the sensitivity, specificity, and predictive values of seven osteoporosis screening tools in populations such as postmenopausal women, older adults, and patients with specific diseases. These tools offer advantages, including high sensiti…
  pubmed Zhang Y, Duan Z, Liu J, Tian C 等 2026 Jul 20 置信度 0.96 computer sciencemedicineartificial intelligencedata sciencemedical physics
• Pre-operative concerns and post-operative satisfaction: comparing attitudes toward bariatric surgery and medication intervention for weight loss on Reddit.
  Patient perceptions influence the success of bariatric surgery and pharmacologic weight loss therapies, yet many concerns never reach providers during clinic visits. Reddit, a popular online community, offers a window to explore these concerns outside clinical…
  pubmed Del Carmen GA, Patel D, Vu N, Tran A 等 2026 Jul 20 置信度 0.96 medical educationmedical physicsperceptionnatural language processingcs.cl
• Validation of Kawasaki MATCH on a Latin American cohort: application to the REKAMLATINA network.
  Key message: In a large multinational validation study, the Kawasaki MATCH machine-learning clinical decision support tool accurately identified patients with Kawasaki Disease (KD) using data from the REKAMLATINA network.
  pubmed Tremoulet AH, Lam JY, Ulloa-Gutierrez R, Burns JC 等 2026 Jul 20 置信度 0.93 internal medicinemedicinediseaseintensive care medicinemedical physics
• Deep learning model for predicting fracture redisplacement in conservatively treated distal radius fractures using radiographs: a retrospective cohort study.
  Accurate assessment of redisplacement risk in distal radius fractures during initial treatment is crucial for selecting the optimal management plan. Traditional clinical decision rules have limited predictive performance. Deep learning models have demonstrated…
  pubmed Dissaneewate P, Thanavirun P, Tangjaroenpaisan Y, Orapiriyakul W 等 2026 Jul 20 置信度 0.96 medicineartificial intelligencecomputer sciencecs.lgmachine learning
• Deep learning for multimodal physiological signal based assessment of sleep disordered breathing.
  Sleep disordered breathing (SDB) is commonly assessed using polysomnography (PSG), which records multiple physiological signals during sleep. Accurate automated assessment of SDB related breathing abnormalities remains challenging because respiratory events oc…
  pubmed Zhang N, Wang F, Sui W, Huang M 等 2026 Jul 20 置信度 0.96 artificial intelligencecomputer sciencecomputer and information sciencescs.lgbrain-computer interface
• Multiparametric MRI Radiomics-Based Interpretable Machine Learning Model for the Prediction of Lymphovascular Space Invasion in Endometrial Cancer.
  To develop and validate a machine learning model combining multiparametric Magnetic Resonance Imaging (MRI) radiomics and clinical indicators for predicting lymphovascular space invasion (LVSI) in endometrial cancer (EC).
  pubmed Meng W, Dou H, Yin J, Ma W 等 2026 Jul 20 置信度 0.93 diseasemedical physicsconvolutional neural networkinterpretabilitycancer
• Bisphenol A drives the comorbidity of non-alcoholic fatty liver disease and osteoarthritis by targeting RHOB: Integrated multi-omics, single-cell analysis, and experimental validation.
  This study focuses on exploring the co-morbid mechanisms by which Bisphenol A (BPA) induces non-alcoholic fatty liver disease (NAFLD) and osteoarthritis (OA).
  pubmed Di J, Wang S, Guo Z, Di Y 等 2026 Oct 1 置信度 0.89 intensive care medicinemicrobiologyinternal medicineblockchaindisease
• Machine Learning Prediction of Liver Fibrosis in Patients With Metabolic Dysfunction-Associated Steatotic Liver Disease.
  Accurate staging of liver fibrosis is crucial for risk stratification in patients with metabolic dysfunction-associated steatotic liver disease. We aimed to develop and validate artificial intelligence-based models capable of distinguishing fibrosis stages.
  pubmed Petta S, Pennisi G, Celsa C, Messaoudi S 等 2026 Jul 20 置信度 0.93 intensive care medicineinternal medicinemedicinemedical physicsdisease
• Preoperative prediction of progesterone receptor expression in meningiomas based on diffusion weighted imaging habitat analysis and Transformer-Based deep learning.
  This study aims to develop and validate a model based on diffusion-weighted imaging (DWI) habitat analysis and Transformer-based deep learning (DL) for preoperative prediction of progesterone receptor (PR) expression in meningiomas.
  pubmed Gui Y, Diao J, Zhang F, Hu W 等 2026 Jul 17 置信度 0.89 convolutional neural networkmathematics educationeess.speess.ivdeep learning
• Linear screening and machine learning to identify suitable candidates for active breathing control after mastectomy in left-sided breast cancer.
  To evaluate the dosimetric benefit of deep inspiration breath-hold (DIBH) using the Active Breathing Coordinator (ABC) for left-sided breast cancer radiotherapy and to identify patients most likely to benefit based on free-breathing (FB) anatomical and clinica…
  pubmed Zheng C, Zhang J 2026 Aug 置信度 0.93 medical physicsmedicineinternal medicinecancerintensive care medicine
• Digital health technologies versus traditional methods for cardiovascular risk assessment in asymptomatic adults: a systematic review and network meta-analysis of diagnostic accuracy and clinical outcomes.
  Cardiovascular disease (CVD) remains the leading cause of mortality worldwide, accounting for approximately 17.9 million deaths annually. Traditional risk assessment tools demonstrate limited discriminatory capacity. Digital health technologies, including AI a…
  pubmed Wang J, Li X, Luo C, Ren Q 2026 Nov 1 置信度 0.93 diseasemedicineintensive care medicineinternal medicinehealth care
• AI agents in drug discovery: A review of evolution, applications, and future directions.
  Artificial intelligence (AI) agents represent a paradigm shift in pharmaceutical research, moving the field from narrow drug-protein affinity modeling toward systems-biology-level evaluation in which autonomous, multi-domain agents combine pattern recognition …
  pubmed Das S, Ferdaus MM, Dam T 2026 Oct 置信度 0.96 artificial intelligencecomputer sciencecs.aidata sciencedrug discovery
• A semi-supervised deep learning and IoMT framework for robust prostate cancer grading under imperfect histopathology data conditions.
  Deep learning has shown remarkable promise in histopathological cancer diagnostics; however, its performance heavily depends on the availability of large-scale, high-quality labelled data, which is often an unrealistic assumption in clinical practice. To addre…
  pubmed Ahmed I, Zhang J, Cirstea S, Jeon G 2026 Oct 置信度 0.96 computer sciencecomputer and information sciencesartificial intelligencemachine learningcs.lg
• A rapid detection of early-stage cervical cancer using nucleus and cytoplasm-based machine learning-driven refractive index surface plasmon resonance biosensor with ZnO-ag efficient materials.
  Cervical cancer is one of the most common cancers in women around the globe and death from such cancer is largely due to late or insufficient diagnosis. Traditional forms of screening like Pap smears and HPV testing, though common with extensive use, have limi…
  pubmed Kamani T, Patel SK, Sharma Y, Al-Zahrani FA 2026 Dec 15 置信度 0.96 medicinegeologycomputer sciencebrain-computer interfacephysical medicine and rehabilitation
• Artificial intelligence (AI) uses in stereotactic radiosurgery (SRS): diagnosis with brain metastasis (BM) - A systematic review.
  Brain metastases (BM) are the most common intracranial tumors in adults, and stereotactic radiosurgery (SRS) has become a mainstay of management. However, several diagnostic challenges persist in the SRS pathway, particularly the differentiation of radiation n…
  pubmed Desai SP, Hori YS, Lam FC, Zagzoog N 等 2026 Jul 20 置信度 0.96 medicinemedlineartificial intelligencemedical physicscomputer science
• The role of artificial intelligence in clinical trials in adult and pediatric rheumatology.
  The development of clinical trials is limited by high costs and methodological complexities. In this context, artificial intelligence (AI) is emerging as a key instrument for their optimization. In the early phases of study design and recruiting, generative AI…
  pubmed La Bella S, Rebollo-Giménez AI, Alongi A, Capitoli G 等 2026 Jul 20 置信度 0.96 medicinecomputer sciencehealth caredata sciencemedical physics
• Multimodel Interpretable Machine Learning for Osteoporosis Prediction in Diabetes Using a Large Critical Care Electronic Health Record Database.
  Diabetes mellitus is associated with increased skeletal fragility and elevated fracture risk; however, early identification of osteoporosis (OP) in diabetic populations remains challenging. This study aimed to develop and compare multiple machine-learning (ML)…
  pubmed Cheng D, Zhang W, Chen J, Zhu X 2026 Jun 30 置信度 0.96 medicineinternal medicineartificial intelligencecomputer sciencemedline
• A feature-efficient dual-task machine learning framework for predicting bone mineral density and osteoporosis stratification in resource-constrained environments.
  Osteoporosis is a chronic skeletal disorder characterized by progressive bone mineral density (BMD) loss and structural deterioration, significantly increasing fracture risk. Despite its high prevalence, early detection remains challenging due to its asymptoma…
  pubmed Maryum A, Shaukat A, Yousaf E, Haque A 等 2026 置信度 0.96 medicineartificial intelligencecomputer sciencemachine learningcs.lg
• Automated Machine Learning Model for Non-Alcoholic Fatty Liver Disease Prediction and External Cohort Validation.
  Non-alcoholic fatty liver disease (NAFLD) is a common liver disorder associated with obesity, insulin resistance, and metabolic syndrome, often going undiagnosed until advanced stages. Traditional diagnostic methods, including imaging and liver biopsy, have li…
  pubmed Li M, Li Y, Chen L, Chen H 等 2026 Jul 3 置信度 0.96 artificial intelligencecomputer sciencemedicinecs.lgcs.ai
• Delusion Is Not a Bug: AI, Psychiatry, and the Ethics of Uncertainty.
  Recent debates about AI "guardrails" in mental health have framed a problem as one of detecting delusion. This paper argues that such framing misunderstands both psychiatry and large language models. In clinical practice, delusion is not simply a false belief …
  pubmed Carr BR 2026 Jul-Aug 置信度 0.96 cs.aiepistemologyengineering ethicslarge language modelsartificial intelligence
• Explainable machine learning for automated robotic surgical skill assessment using rich kinematic features.
  Robotic-assisted surgery (RAS) extends minimally invasive surgery by restoring dexterity, tremor filtration, and ergonomic console control compared with open procedures and conventional laparoscopy. Objective, scalable skill assessment from console kinematics …
  pubmed Xuan W, Rui Z, Mingxu Y, Azam M 等 2026 Jul 20 置信度 0.96 medicineartificial intelligencecomputer and information sciencesscience policymachine learning
• Mapping the evolution of deep learning and computer vision in robotic surgery: a bibliometric analysis of surgical video intelligence, instrument perception, and clinical translation.
  Deep learning and computer vision are increasingly embedded in robotic surgery, yet the development and translational direction of this research domain remain incompletely characterized. We conducted a bibliometric and visualization analysis of publications re…
  pubmed Yang D, Shang F, Xu Y, Liu J 等 2026 Jul 20 置信度 0.96 artificial intelligencemedicinescience policydata sciencemedline
• Discovery of a DNA methylation episignature for Weiss-Kruszka syndrome.
  Weiss-Kruszka syndrome (WSKA; OMIM 618619) is a rare autosomal dominant neurodevelopmental disorder caused by haploinsufficiency of ZNF462, a zinc-finger transcription factor involved in chromatin regulation and early embryonic development. WSKA is characteriz…
  pubmed McConkey H, van der Laan L, Ghosh S, Kleinendorst L 等 2026 Jul 20 置信度 0.96 medicinebiologygeneticspharmacologybiological sciences
• Multimodal prediction of metachronous liver metastasis in stage I-III colorectal cancer patients: multicenter cohort study employing machine learning.
  Postoperative metachronous liver metastasis (MLM) in colorectal cancer (CRC) patients is often difficult to predict using conventional clinical and radiological methods, which may result in delayed diagnosis and treatment. We aimed to develop and validate an a…
  pubmed Liang L, Zhang Y, Yang L, Li J 等 2026 Jul 20 置信度 0.93 medicinemedical physicsmedlinecancerinternal medicine
• Development and validation of a LightGBM based machine learning model for predicting postoperative erectile dysfunction after robot assisted radical prostatectomy: a multicenter cohort study.
  Postoperative erectile dysfunction remains a highly debilitating complication following robot assisted radical prostatectomy for localized prostate cancer. Traditional risk stratification heavily relies on anatomical and oncological parameters utilizing simple…
  pubmed Wang K, Wang M, Zheng W, Zhang H 等 2026 Jul 20 置信度 0.96 medicineinternal medicineartificial intelligencepsychologycomputer science
• Neural network-enhanced investigation of ferroptosis and druggability in early-onset alzheimer's disease.
  Alzheimer's disease (AD) is a complex neurodegenerative disorder which is multifactorial in nature. Some of its characteristics are slow cognitive decline, memory problems and behavioral changes. AD patient brains show a progressive synaptic toxicity, autophag…
  pubmed Singh P, Rath SL 2026 Jul 20 置信度 0.96 medicineneurosciencepsychologybiotechnologybiological sciences not elsewhere classified
• Comparison of large language models in the management of pediatric ureteropelvic junction obstruction: a comparative analysis of 125 clinical scenarios.
  To evaluate and compare the clinical accuracy, reliability, comprehensiveness and readability of three prominent Large Language Models (LLMs) (ChatGPT, Gemini, and Copilot) in the management of pediatric ureteropelvic junction obstruction.
  pubmed Baloğlu İH, Karlı G, Çekmece AE, Özgür MÖ 等 2026 Jul 20 置信度 0.93 large language modelsmedical physicscs.clnatural language processinggenerative grammar
• [Endometriosis pain research in Germany : ENDO-PAIN and StEPP-UPP-two new research consortia on endometriosis pain].
  Endometriosis is one of the most common causes of chronic pelvic or lower-abdominal pain, yet mechanisms, predictors, and patient-centered treatment pathways remain insufficiently defined. This article summarizes the situation in Germany and presents two compl…
  pubmed Velho RV, Pradier B, Werner F, Pogatzki-Zahn EM 等 2026 Aug 置信度 0.96 medicinediseaseinterpretabilitycancermedline
• Development and Validation of an Early Risk Prediction Model for Sepsis-Induced Coagulopathy Based on Machine Learning.
  ObjectiveTo develop and validate machine learning models for early prediction of sepsis-induced coagulation dysfunction (SIC) risk at intensive care unit (ICU) admission, before diagnostic criteria are fully met.MethodsThis retrospective cohort study enrolled …
  pubmed Yang Q, Fang L, Ren C, Xiong W 等 2026 Jan-Dec 置信度 0.96 medicinebiological sciences not elsewhere classifiedinternal medicinebiotechnologyartificial intelligence
• Combining MRI-Derived Imaging Measures and Peripheral Proteomics to Improve the Mechanistic Understanding of Alzheimer's Disease Beyond Core Pathology: A Scoping Review.
  Alzheimer's Disease (AD) core pathology involves amyloidβ and ptau, leading to neurodegeneration (ATN model), yet individuals with comparable core pathology show considerable biological and clinical heterogeneity, motivating new models that consider non-…
  pubmed Li OY, Herrera Guerra D, Anthony M, Oh K 等 2026 Jul 17 置信度 0.96 medicinediseaseneuroimagingneuroscienceinterpretability
• Development of An Explainable Machine Learning Model for Predicting Fatigue in Rheumatoid Arthritis.
  Fatigue has been identified as one of the common symptoms among people who have rheumatoid arthritis (RA), which has a significant impact on their quality of life (QoL). Although fatigue has been identified as a symptom, few predictive models using clinical in…
  pubmed Ma Y, Zhang Y, He Y, Zhao L 等 2026 Jul 17 置信度 0.93 biotechnologyscience policybiological sciences not elsewhere classifiedintensive care medicinedisease
• Computational strategies for allosteric drug discovery: from cryptic pocket detection to rational design.
  Allostery offers a powerful route to regulate protein function and expands drug discovery beyond the orthosteric paradigm. By acting at sites distinct from the active site, allosteric modulators can achieve greater selectivity, reduce off-target effects, and o…
  pubmed Mukhopadhyay S, Chakrabarty S 2026 Aug 4 置信度 0.96 drug discoverycomputational biologycomputer sciencecs.aicomputer and information sciences
• Artificial Intelligence in the Nutritional Management of Inflammatory Bowel Disease: A Scoping Review.
  Diet is closely associated with the onset, progression, and prognosis of inflammatory bowel disease (IBD). In the absence of specific dietary and nutritional guidelines, nutritional management for IBD patients is fraught with challenges and uncertainties. Exis…
  pubmed Qian X, Yu J, Zhang Q, Jia G 等 2026 置信度 0.96 medicineintensive care medicineinternal medicinediseasepsychological intervention