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• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• [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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• [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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• Machine learning-based diagnosis of movement disorders using clinical neurophysiology: are we ready?
  pubmed Grippe T 2026 Oct 置信度 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.82
• 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 0.66