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• Telemedicine use among physicians in the German outpatient sector: A secondary analysis of a cardiologist-dominated web-based survey with Bayesian model averaging and exploratory machine learning.
  Cardiovascular diseases remain a major health burden in Germany, and telemedicine (TM) offers promising solutions for outpatient care, yet barriers limit uptake. While prior studies relied on qualitative or conventional statistical methods, they often struggle…
  pubmed Petit P, Vuillerme N, Gehrmann J, Stephan J 等 2026 Jan-Dec 置信度 0.82
• Techniques, Performance, and Feasibility of Natural Language Processing for Abstract Screening in Evidence Synthesis: A Systematic Review.
  Natural language processing (NLP) techniques offer promising solutions for semi-automating the time-consuming process of abstract screening in systematic reviews. The exponential growth of published literature has created significant bottlenecks, with review t…
  pubmed Shankar R, Goh Z, Xu Q 2026 Sep 置信度 0.82
• A mitoxyperilysis-related signature stratifies prognosis and identifies an aggressive colorectal cancer ecosystem with immune remodeling.
  Mitoxyperilysis is a recently described lytic cell death pathway linked to innate immune activation and metabolic disruption. Its clinical and biological relevance in colorectal cancer (CRC) remains unclear. This study aimed to develop a mitoxyperilysis-relate…
  pubmed Zhang Y, Sun B, Lin J, Ding C 等 2026 置信度 0.82
• Construction and verification of an early warning model for hypothermia in emergency trauma patients based on the random forest method.
  To construct an early warning model for hypothermia in emergency trauma patients using Random Forest (RF) and compare its predictive performance with Logistic regression.
  pubmed Cao J, Mu X, Zhu H, Liu Y 2026 置信度 0.82
• Machine learning-based methods in diagnosing cardiac amyloidosis: a meta-analysis.
  Cardiac amyloidosis (CA) is an infiltrative restrictive cardiomyopathy characterized by the deposition of β -fold amyloid, often presenting as left ventricular hypertrophy. Early nonspecific symptoms lead to frequent misdiagnosis as hypertrophic cardiomy…
  pubmed Song Y, Wang Q, Jia L, Pei Y 2026 置信度 0.82
• Potential of Image2Image translation in reducing AI bias attributed to differences in CT reconstruction methods: proof-of-concept study on a paired dataset.
  The choice of image reconstruction approach, such as Iterative Model Reconstruction (IMR) and iDose 4 , is critical in computed tomography (CT) as distribution shifts between them can introduce systematic bias in clinical AI models, posing a barrier to efficie…
  pubmed Li F, Caldeira LL, Jaiswal A, Hokamp NG 等 2026 置信度 0.82
• Microbiome and cancer: mechanistic insights, diagnostic potential, and therapeutic strategies.
  The human microbiome is now recognized as an active and dynamic participant in cancer biology rather than a passive bystander. Increasing evidence demonstrates that microbial dysbiosis contributes to tumor initiation and progression through chronic inflammatio…
  pubmed Kumar V, Chaudhary A, Gautam M, Verma P 等 2026 置信度 0.82
• Development and validation of an interpretable machine learning-based predictive model for breast cancer bone metastasis.
  Breast cancer is one of the most common malignancies worldwide, with bone metastasis representing its most frequent distant metastatic form, significantly worsening patient prognosis. This study aims to develop a machine learning-based predictive model for acc…
  pubmed Fan C, Tian M, Ding Z, Peng J 等 2026 置信度 0.82
• Artificial intelligence for genomic science: a scoping review of concepts, architectures, applications, and open challenges.
  Artificial intelligence (AI) is becoming central to genomics and multi-omics, but its concepts, architectures, applications, evaluation standards, and translational requirements remain fragmented. This scoping review mapped how AI is defined and operationalize…
  pubmed Rodrigues WF, Parise MTD, Parise D, Dos Santos LM 等 2026 置信度 0.82
• A lightweight DeepME model based on improved YOLOv11 architecture for macular edema detection and treatment monitoring.
  We developed and validated an improved YOLOv11-based deep learning algorithm for accurate macular edema detection in optical coherence tomography (OCT) images, and built DeepME-a lightweight system for diagnosis and treatment recommendations.
  pubmed Bai X, Yi M, Chen T, Feng N 等 2026 置信度 0.82
• A machine learning model for 90-day mortality prediction in hepatitis B virus-related acute-on-chronic liver failure: the pivotal role of CALLY index.
  Hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF) is a life-threatening syndrome, the condition can deteriorate rapidly, and the 90-day mortality rate is high. Due to the rapid changes in the clinical course, early and accurate risk stratific…
  pubmed Zhang Y, Li C, Su S, Huang J 等 2026 置信度 0.82
• Identifying risk factors for drug use recurrence with ecological momentary assessment, wearable technologies, and machine learning: a feasibility trial of peer recovery support specialist intervention.
  Identifying predictors of relapse/drug use recurrence (DUR) in real-time could allow the rapid implementation of overdose prevention interventions for those with substance use disorders (SUD). Wearable devices and phone-based applications for self-reported ass…
  pubmed Mahoney Iii JJ, Finomore VS, Marton JL, England LJ 等 2026 置信度 0.82
• Artificial intelligence in drug discovery: from algorithmic foundations to clinical translation.
  Artificial intelligence is quietly reconfiguring the landscape of drug discovery. It sharpens the search for new targets, refines lead compounds, and helps tailor clinical trial designs. Behind these advances sits a family of methods-convolutional, recurrent, …
  pubmed Mao Z, Yan L 2026 置信度 0.82
• Upregulated CD177 on neutrophils is implicated in sepsis pathogenesis and necroptosis-driven inflammation.
  Sepsis remains a leading cause of mortality in critical care, with dysregulated inflammatory responses driving disease progression. However, the role of necroptosis in sepsis pathogenesis remains incompletely understood.
  pubmed Liu H, Cheng X, Li J, Wei W 等 2026 置信度 0.82
• Early multi-cancer detection using liquid biopsy: emerging biomarkers and clinical strategies.
  Liquid biopsy has become a revolutionary method for the early detection of cancer as a non-invasive technology that can assess circulating tumor material in biofluids. Liquid biopsy allows dynamic monitoring of tumor evolution, genetic changes and treatment re…
  pubmed Nirob SR, Morol MK, Rahman D, Hui LT 等 2026 置信度 0.82
• Metabolomic Profiling and Machine Learning-Based Prediction of High-Dose Methotrexate-Induced Liver Injury in Pediatric Acute Lymphoblastic Leukemia.
  High-dose methotrexate (HD-MTX) is essential for pediatric acute lymphoblastic leukemia (ALL) but frequently causes hepatotoxicity. To address the critical lack of early prediction tools, this study investigated untargeted metabolomic profiles to identify pred…
  pubmed Guo K, Wang L, Feng X, Yang J 等 2026 Sep 置信度 0.82
• Exploring the Prevalence and Key Predictors of Probable Depression Among Parents and Primary Caregivers of Children and Adolescents With Specific Learning Disorders in the Kingdom of Saudi Arabia: A Cross-Sectional Explainable Machine-Learning Study.
  This study estimated the prevalence of probable depression among parents and primary caregivers of children and adolescents with specific learning disorders (SLDs) in Saudi Arabia and developed explainable machine-learning models for screening-oriented classif…
  pubmed Almulla AA, Khasawneh MAS 2026 Jul-Aug 置信度 0.82
• Machine learning-optimized discharge timing in typhoid care: Implications for clinical outcomes, cost efficiency, and health system performance.
  To develop and validate a machine learning model identifying typhoid fever patients at risk of unnecessarily prolonged hospitalization, and to quantify the clinical, financial, and systemic consequences of model-guided discharge optimization in a fragmented, m…
  pubmed Momahhed SS, Haghighathoseini A 2026 置信度 0.82
• AI-Assisted Engineering of Glycyrrhizic Acid/Simvastatin Nanocrystals for Multifunctional Treatment of Bacterial Osteomyelitis.
  Bacterial osteomyelitis remains a formidable challenge in clinic because existing monotherapies fail to block inevitable infection, uncontrolled inflammation, and impaired bone regeneration ‌concurrently. Here, we present an AI-assisted strategy that in…
  pubmed Han Y, Zhao Y, Yang C, Niu M 等 2026 Jul 23 置信度 0.82
• Large Language Model Few-Shot Learning for Predicting Individual Treatment Response to Smartphone-Based Mindfulness in Autistic Adults With Anxiety: Secondary Analysis of a Randomized Controlled Trial.
  Anxiety disorders are highly prevalent among adults with autism, with 20%-65% experiencing at least one diagnosable anxiety disorder. While mindfulness-based interventions have demonstrated efficacy for anxiety reduction, treatment response varies considerably…
  pubmed Ahn G, Li CE, Liang A, Choi W 等 2026 Jul 23 置信度 0.82
• Digital phenotyping of CGM engagement reveals distinct glycemic outcomes.
  Benefits from continuous glucose monitors (CGMs) may depend on how devices are used over time-not only how often they are used. We linked one year of device-generated CGM wear data from 2,351 U.S. Veterans to electronic health records (EHRs) to characterize re…
  pubmed Zhang B, Okuno T, Li E, Riggins E 等 2026 Jul 置信度 0.82
• Initial-Visit Specialty Triage in Rare Diseases Using Large Language Models: Retrospective Benchmarking Study.
  Specialty triage at first contact is an overlooked step in early diagnostic pathways for rare diseases. Patients often present with overlapping, multisystem, and atypical manifestations, making first-visit specialty selection challenging and potentially prolon…
  pubmed Song J, Xu Z, Xiao M, Bi C 等 2026 Jul 23 置信度 0.82
• Model and Task-Aware Test-Time Scaling Strategies for Large Language and Vision-Language Models in Medicine: Evaluation Study.
  Test-time scaling has emerged as a promising method to enhance the reasoning capabilities of large language models (LLMs) and vision-language models (VLMs) during inference without additional training. While foundational studies established scaling paradigms i…
  pubmed Oh G, Kim S, Park S, Kim BH 2026 Jul 23 置信度 0.82
• Mass-Spectrometry-Identified Quality Markers of Jingtong Granules Are Predicted to Engage Upregulated Neutrophil Granule Enzymes in Cervical Spondylotic Radiculopathy: An Integrative Machine-Learning and Molecular-Dynamics Study.
  Jingtong Granules is a clinically approved seven-herb formula for CSR, a condition in which radicular pain is sustained partly by inflammatory and immune processes, yet the immune-cellular state of CSR and the immune-level mechanism of the formula remain poorl…
  pubmed Yang G, Han C, Li H, Chang L 等 2026 Oct 15 置信度 0.82
• Predicting KRT or Death in Critically Ill Patients with Rhabdomyolysis Using Machine Learning: A Multicenter Study.
  Rhabdomyolysis is associated with outcomes ranging from muscle injury to AKI, KRT, and death. Early identification of patients at highest risk of severe outcomes may help inform triage, monitoring, and nephrology consultation. We aimed to develop and externall…
  pubmed Mercier J, Sharma A, Boseovski J 2026 Jul 23 置信度 0.82
• Surface-Engineered Carbon Nanotubes Aerogel Sensor Array Enabled AI-Driven Selective Detection of Biomarker VOCs: A Proof-of-Concept in Simulated Humid Mixtures.
  Selective detection and quantitative analysis of biomarker volatile organic compounds (VOCs) in complex gas mixtures remain a major challenge for noninvasive breath diagnostics due to wide concentration variability and strong humidity interference. Here, a del…
  pubmed Rohilla R, Alexander R, Sawant SG, Dasgupta K 等 2026 Jul 23 置信度 0.82
• Multimodal features and prognostic risk assessment in locally advanced gastric cancer patients following neoadjuvant therapy based on machine learning algorithms: a multicenter study.
  Neoadjuvant therapy (NAT) is recommended for locally advanced gastric cancer (LAGC), but some patients respond poorly. We aimed to construct a multimodal model integrating CT images, transcriptomic sequencing, and clinicopathological data to assess prognosis i…
  pubmed Liu L, Zhong Q, Weng C, Chen L 等 2026 Sep 置信度 0.82
• Integrated machine learning and structural bioinformatics guided identification of novel molecular scaffolds as renin inhibitors.
  Cardiovascular diseases (CVDs) remain the leading cause of death globally, with hypertension as its critical hallmark. The Renin-Angiotensin-Aldosterone-System (RAAS) plays a central role in regulating blood pressure, highlighting its relevance for antihyperte…
  pubmed Talware SK, Bhati G, Srivastava G, Shukla S 等 2026 Jul 23 置信度 0.82
• Large-Scale Plasma Proteomics Profiles for Predicting Atrial Fibrillation Associated Stroke Risk : Type of manuscript: Original Research.
  Stroke is a major complication of atrial fibrillation (AF), and risk prediction using the congestive heart failure, hypertension, age, diabetes, stroke, vascular disease, and sex category score (CHA₂DS₂-VASc) remains limited by residual heterogen…
  pubmed Huang S, Feng X, Wu H, Liang R 等 2026 Jul 23 置信度 0.82
• Continuous imputation of blood gas and metabolic panel laboratory values in the intensive care unit using machine learning.
  We developed machine learning (ML) models to perform continuous hourly prediction of arterial blood gas (ABG) and basic metabolic panel (BMP) laboratory values in critically ill patients. We evaluated its impact on prediction of the need for renal replacement …
  pubmed Mamandipoor B, Krause M, Korti P, Hsu CN 等 2026 Jul 23 置信度 0.82
• Integrative multi-omics analysis unravels the metabolic landscape and reveals serum biomarkers for early diagnosis of hyperuricemia.
  Hyperuricemia (HUA) is a major risk factor for gout and multiple metabolic disorders. Although serum uric acid (UA) is the gold standard for HUA diagnosis, it fails to reflect early metabolic disturbances and shows limited predictive value for asymptomatic HUA…
  pubmed Sun X, Gong B, Sun Y, Sun H 等 2026 Jul 23 置信度 0.82
• Integrative multi-omics reveals NQO1-mediated airway epithelial injury as a key mechanism of bisphenol A-induced COPD.
  Bisphenol A (BPA) is a ubiquitous environmental pollutant, but its relationship with chronic obstructive pulmonary disease (COPD) and the underlying toxicological mechanisms remain unclear. To address this, we employed an integrative multi-omics strategy that …
  pubmed Li R, Ge S, Liu J, Li Y 等 2026 Jul 23 置信度 0.82
• Heterogeneity of Treatment Effect of DOACs vs Warfarin in Atrial Fibrillation.
  Direct oral anticoagulants (DOACs) are recommended over vitamin K antagonists (VKAs) for stroke prevention in atrial fibrillation (AF). However, limited accessibility in resource-constrained settings makes it important to identify patient subgroups in whom VKA…
  pubmed Al Said S, Bellavia A, Braunwald E, Hylek EM 等 2026 Jul 置信度 0.82
• Risk Stratification for Postpartum Hemorrhage in Vaginal Delivery: A Nationwide Cohort Study of Predelivery and Intrapartum Risk Assessment.
  To develop and validate machine learning models for clinically applicable risk stratification of postpartum hemorrhage (PPH) in vaginal delivery, and to assess whether incorporating intrapartum information improves detection while maintaining a similar screeni…
  pubmed Akazawa M, Hashimoto K, Ueno M, Nakabayashi A 等 2026 Aug 置信度 0.82
• The mediating role of genes in the influence of intestinal flora on type 2 diabetes and the screening of diagnostic markers.
  The composition of intestinal flora affects the occurrence and development of type 2 diabetes to some extent, with dysregulation of the microbiome being a clinical manifestation of the disease.
  pubmed Chen YY, Shi YF, Zhang XY, Zhang JY 等 2026 Jul 23 置信度 0.82
• AI-Driven Multi-Omics Integrated Applications Using Diverse Neural Networks for Breast Cancer Diagnostic Screening and Biomarker Discovery.
  Breast cancer (BC) is a highly complex and heterogeneous malignancy and the most prevalent cancer among women worldwide. The diagnosis, prognosis, and the treatment of BC pose significant challenges that are responsible for their limited therapeutic efficacy. …
  pubmed Kumari V, Tiwari H, Singh S, Kailashiya V 等 2026 Jul 23 置信度 0.82
• Integrated spatially guided transcriptomics and multiplex imaging identify a high-risk CD163+/CD11c-subgroup in diffuse large B-cell lymphoma.
  Emerging data identify infiltrating immune cells in diffuse large B‑cell lymphoma (DLBCL) as prognostic biomarkers with tentative implications for therapeutic stratification. To elucidate the tumor immune microenvironment (TIME) and molecular features g…
  pubmed Johansson A, Nilsson D, Wikström F, Olsson LM 等 2026 Jul 23 置信度 0.82
• Evaluation Frameworks for Clinical AI Incorporating Validation Strategies, Real-World Applicability, and Ethical Principles: Scoping Review.
  AI shows substantial potential in health care; however, the absence of standardized evaluation frameworks limits its safe and effective clinical implementation because of inconsistent validation requirements and fragmented ethical principles. Existing guidelin…
  pubmed López Medina DC, Oliveros-Navarro A, Moreno Angel N, Herrera-Arellano AC 等 2026 Jul 22 置信度 0.82
• Optical coherence tomography of the tympanic membrane and middle ear: clinical applications.
  Optical coherence tomography (OCT) is a noninvasive optical imaging technique to image soft tissue and thin bony structures with high resolution, approaching that of histology. This review summarizes recent progress in the clinical application of OCT for tympa…
  pubmed Azimzadeh JB, Applegate BE, Oghalai JS 2026 Jul 23 置信度 0.82
• EEG criticality as a prognostic tool for functional outcomes in sedated pediatric intensive care patients.
  Predicting meaningful recovery in sedated patients remains a major challenge in the pediatric intensive care unit (PICU) due to the lack of reliable, behavior-independent prognostic markers for children. Criticality of electroencephalography (EEG) signals refl…
  pubmed Newman D, Grinberg M, Jones K, Woodward K 等 2026 置信度 0.82
• A novel machine learning approach generates personalized estimates of graft and patient survival to better inform older kidney transplant candidates.
  An information most relevant to patients when deciding to accept a kidney offer is an estimate of its potential longevity. Using a novel machine learning approach, our aim was to develop a model that can output personalized curves estimating kidney graft and p…
  pubmed Boivin PL, Jalbert J, Thériault L, Qi Y 等 2026 置信度 0.82
• Development and validation of an interpretable machine learning model for predicting atrial fibrillation risk in middle-aged and older patients with coronary heart disease.
  Coronary heart disease (CHD) and atrial fibrillation (AF) frequently coexist, yet existing risk stratification tools inadequately capture the nonlinear, multidimensional determinants of AF in middle-aged and older CHD patients. This study aimed to develop and …
  pubmed Chen F, Fu Q, Li L, Zhang X 等 2026 置信度 0.82
• Using artificial intelligence for distinguishing benign and malignant vertebral compression fractures by computed tomography: a scoping review.
  The purpose of this scoping review is to compile the evidence regarding the use of computed tomography (CT) to distinguish between benign and malignant vertebral compression fractures (VCFs) in artificial intelligence (AI) applications.
  pubmed Mohammadrezaee M, Bakhshi R, Khalaji A, Jarideh I 等 2026 置信度 0.82
• Artificial intelligence to enhance research integrity in evidence-based medicine: toward scalable trustworthiness assessment.
  Fraudulent, falsified, and otherwise unreliable clinical research threatens the foundations of evidence-based medicine because systematic reviews, meta-analyses, and clinical practice guidelines depend on the trustworthiness of the studies they include. Retrac…
  pubmed Mo M, Arora R, Cao C, Tricco AC 等 2026 置信度 0.82
• Machine learning-based fetal health prediction and development of smart web application.
  Fetal health monitoring is critical for early identification of pregnancy-related risks. Manual interpretation of cardiotocography (CTG) signals is subjective and variable among healthcare professionals.
  pubmed Puri C, Reddy KTV, Gote PM 2026 置信度 0.82
• Psychological distress, digital behavioral risks, and physical activity as predictors of subjective wellbeing: a machine learning study in a large sample of community-dwelling adults.
  Regular physical activity is a key determinant of psychological wellbeing, yet its interaction with emerging digital behavioral risks remains insufficiently understood. Compulsive internet use and nomophobia have been linked to psychological distress, which ne…
  pubmed Saidane M, Guelmami N, Dhahbi W, Ayachi F 等 2026 置信度 0.82
• A Proposed Clinical Validation Pathway for the Artificial Intelligence-Driven Integrated Risk Assessment of Cardiovascular Disease (AIRA-CVD): A Translational Framework Integrating Inflammatory Biomarkers, Histopathology, and Machine Learning.
  Cardiovascular disease (CVD) remains a leading cause of morbidity, mortality, and healthcare expenditure despite advances in prevention and treatment. The Artificial Intelligence-Driven Integrated Risk Assessment of Cardiovascular Disease (AIRA-CVD) framework …
  pubmed Ogbuefi C 2026 Jun 置信度 0.82
• Development and validation of a clinical-radiomics nomogram for differentiating Mycoplasma pneumoniae pneumonia from bacterial pneumonia in children.
  In this case-control study, we developed a nomogram merging computed tomography (CT)-based radiomics, clinical indicators, and CT imaging findings for differentiating Mycoplasma pneumoniae Pneumonia (MPP) from bacterial pneumonia (BP) in children.
  pubmed Guan Y, Wang X, Song C, Bi L 等 2026 置信度 0.82
• Do nutritional variables improve cardiovascular disease prediction? A comparative machine learning analysis.
  Cardiovascular diseases (CVD) remain a leading cause of mortality worldwide, highlighting the need for accurate prediction models. While machine learning (ML) approaches have shown promising results, the contribution of nutritional variables to prediction perf…
  pubmed Toprak K, Cindiloglu ZU, Sanlier N 2026 置信度 0.82
• Intelligent Rehabilitation: Advances in Artificial Intelligence for Musculoskeletal Rehabilitation: A Narrative Review.
  Musculoskeletal diseases, such as osteoarthritis and joint trauma, significantly impact patient mobility, independence, and quality of life. With the rising demand for effective and accessible rehabilitation strategies, artificial intelligence (AI) has emerged…
  pubmed Hao J, Sun S, Dou T, Deng J 等 2026 置信度 0.82
• Prediction of acute postoperative protein depletion risk in colon cancer using an in-context learning foundation model: a retrospective cohort study.
  Acute postoperative protein depletion, including hypoalbuminaemia and hypoproteinaemia, frequently complicates colon cancer surgery and exacerbates adverse outcomes, yet early risk stratification remains challenging.
  pubmed Cao X, Han L, Zan X, Zhang Y 等 2026 置信度 0.82
• Emotion recognition from multimodal biosignals: supervised and unsupervised machine learning approaches based on EEG and GSR.
  Artificial intelligence (AI) and machine learning (ML) are increasingly applied in psychology, particularly in educational and clinical settings, to analyse complex behavioural and physiological data. However, evidence regarding the capacity of multimodal phys…
  pubmed Sáiz-Manzanares MC, Marticorena-Sánchez R 2026 置信度 0.82
• Prediction models for progression from prediabetes to diabetes: a systematic review and meta-analysis.
  Prediabetes increases the risk of type 2 diabetes mellitus (T2DM). Accurate prediction is crucial for early prevention, but evidence on prediction models has not been comprehensively synthesized. This study systematically evaluated the accuracy of such models …
  pubmed Wang Y, Wang C, Wang J 2026 置信度 0.82
• Integrative bioinformatics analysis identifies placental senescence-associated signatures in early-onset preeclampsia.
  Early-onset preeclampsia (EOPE) is a severe hypertensive disorder of pregnancy associated with preterm delivery and maternal multi-organ dysfunction. Although placental senescence and immune dysregulation have been implicated in EOPE, the expression profile of…
  pubmed Lin L, Chen Y, Chen L, Gu S 等 2026 置信度 0.82
• Risk prediction of pediatric intensive care unit admission in children with respiratory syncytial virus infection using interpretable machine learning.
  Respiratory syncytial virus (RSV) is a major cause of pediatric acute lower respiratory infection. Early prediction of pediatric intensive care unit (PICU) transfer may support clinical decision-making and resource allocation. We aimed to develop and temporall…
  pubmed Dong J, Ni J, Zhao M, Du Z 等 2026 置信度 0.82
• Development and validation of an interpretable machine learning model for venous thromboembolism risk prediction in patients with lung cancer: a real-world study.
  Venous thromboembolism (VTE) is a common complication in patients with lung cancer and remains difficult to predict accurately using existing risk assessment tools. This study aimed to develop and validate a machine learning model for individualized prediction…
  pubmed Xia A, Liu J, Song J, Han Y 等 2026 置信度 0.82
• Perioperative nutritional support is associated with attenuated early postoperative albumin decline after gastrectomy for gastric cancer: a retrospective cohort study and machine learning prediction model.
  Perioperative nutritional support is recommended for surgical patients at nutritional risk, but its relationship with early postoperative serum albumin recovery after gastrectomy for gastric cancer remains uncertain, and clinicians lack practical tools to iden…
  pubmed Wen T, Zhang X, Zhang X, Lv S 等 2026 置信度 0.82
• Integrating chemotherapy, radiotherapy, and O6-methylguanine-DNA methyltransferase (MGMT) status with deep-learning cellular tumor volumetry sharpens prediction of glioblastoma recurrence on postoperative MRI.
  Distinguishing glioblastoma recurrence from posttreatment effects on magnetic resonance imaging (MRI) remains a major diagnostic challenge. While recent models consider O6-methylguanine-DNA methyltransferase (MGMT) status, most machine learning models addressi…
  pubmed Belbadaoui T, Forester A, Khalvati F, Gagnon L 2026 Jan-Dec 置信度 0.82
• Radiomics-based machine learning to evaluate immunotherapy efficacy in non-small cell lung cancer patients with bone metastases.
  Assessing treatment response in bone metastases from non-small cell lung cancer (NSCLC) remains a major clinical challenge, particularly for patients receiving immune checkpoint inhibitors (ICIs). The existing response criteria are not optimized for osseous di…
  pubmed Kakavand R, Forkert ND, Abbott A, Kendal J 等 2026 Jul 置信度 0.82
• A novel interpretable machine learning framework for predicting postpartum depression: a SHAP-based analysis of maternal and infant health indicators.
  Postpartum depression (PPD) affects nearly 20% of women globally. Conventional regression models often have limited predictive accuracy.
  pubmed Lv F, Li S, Yuan X, Ma Y 等 2026 置信度 0.82
• Genomic variant-driven prediction of azole resistance in Aspergillus fumigatus using GWAS and machine learning.
  Azole resistance in Aspergillus fumigatus , a major cause of invasive aspergillosis, threatens public health. Known drivers include cyp51A/B mutations (e.g., TR34/L98H and TR46/Y121F/T289A), yet existing studies have largely focused on clinical isolates and kn…
  pubmed Li D, Yue X, Hu W, Zhong H 等 2026 置信度 0.82
• Identification of key targets driving biofilm formation and virtual screening of potential inhibitors in Pseudomonas aeruginosa.
  Pseudomonas aeruginosa , a member of the "ESKAPE" pathogens, possesses a robust ability to form biofilms-a key factor that contributes to its antibiotic resistance and poses significant challenges for clinical management. Identifying potential therapeutic targ…
  pubmed Wang R, Mo E, Wen J, Chen G 等 2026 置信度 0.82
• Machine Learning Classification of Serum miR-210 as a Biomarker of Exercise Training Response.
  MicroRNAs (miRNAs) in circulating blood are increasingly recognized as biomarkers of exercise-induced physiological adaptation. Of these, miR-210, a hypoxiainducible miRNA associated with angiogenesis, mitochondrial control, and cellular stress response, has s…
  pubmed AlMatar M, Mourgan FHAE, Al Shamli A, Ahmed Hefny NED 等 2026 Jul 13 置信度 0.82
• Prediction of Chemical-induced Autonomic Neurotoxicity with Machine Learning Approaches.
  Autonomic neurotoxicity associated with chemical exposure represents a significant clinical and safety concern. Traditional assessment relies on in vivo methods that are costly and time-consuming, and few computational tools specifically address this endpoint.…
  pubmed Kuang ZK, Huang Q, Duan X 2026 Jul 13 置信度 0.82
• Applications of Artificial Intelligence in Oral Radiology and Diagnosis: A Scoping Review.
  This scoping review evaluates the role of artificial intelligence, including deep learning and machine learning methods, in diagnostic applications within oral and maxillofacial radiology. The review covers panoramic and cephalometric radiographs, cone-beam co…
  pubmed Riyaz SSMA, Almutairy MF, Mohsin SF, Almutairi BM 2026 Jul 22 置信度 0.82
• Fast Submillimeter Whole-Brain T(2)*-Weighted Imaging Using 3D-EPI With CAIPIRINHA and Deep-Learning Denoising at 3T.
  Recent updates to the diagnostic criteria of multiple sclerosis (MS) require whole-brain T 2 *-weighted (T 2 *w) imaging with submillimeter resolution to detect novel diagnostic biomarkers such as the central vein sign. However, to achieve the needed submillim…
  pubmed Nair SM, Quah B, Song JW, Jin J 等 2026 Nov 置信度 0.82
• clinTALL: machine learning-driven multimodal subtype classification and treatment outcome prediction in pediatric T-ALL.
  Childhood T-lineage acute lymphoblastic leukemia (T-ALL) is an aggressive hematologic malignancy with poor prognosis. Differently from B-cell precursor ALL, T-ALL lacks effective risk stratification strategies. A recent study has integrated whole genome and wh…
  pubmed Stoiber L, Antić Ž, Rebellato S, Fazio G 等 2026 Jul 22 置信度 0.82
• Correction: Diagnostic performance of machine learning and deep learning algorithms for thyroid cancer metastasis: a systematic review and meta-analysis.
  pubmed Lichahi MA, Anvari S, Hemmati H, Zadgari E 等 2026 Jul 23 置信度 0.82
• The use of artificial intelligence and machine learning to predict tumor recurrence in high-grade gliomas: a systematic review.
  High-grade gliomas (HGGs) are aggressive tumors with a propensity for recurrence. Despite standardized therapies, definitive treatment is elusive. Advancements in artificial intelligence (AI) and machine learning (ML) can potentially identify recurrence probab…
  pubmed Kite T, Nayak T, Jaffee S, Porwal M 等 2026 Jul 23 置信度 0.82
• Artificial intelligence in impurity prediction: current landscape, challenges, and future directions.
  Earlier identification, regulation of impurities in pharmaceutical products is critical throughout the medication development process because they have a high impact on drug quality, safety, and regulatory approval. Traditional analytical methods like LC-MS an…
  pubmed Thombre S, Bonde C, Bhole R, Gawad J 等 2026 Jul 23 置信度 0.82
• "Hermeneutic burden" and clinical responsibility: a response to Sparrow et al. on explanation and machine learning.
  This paper critically reviews Sparrow et al.'s notion of the "hermeneutic burden" placed upon clinicians by the demand for explainable artificial intelligence (XAI) in the context of adaptive machine learning (ML) systems. While Sparrow et al. highlight import…
  pubmed Adams J 2026 Jul 23 置信度 0.82
• Early Detection of Cognitive Impairment Using Time-Frequency Analysis of Fine Motor Accelerometry.
  Early detection of cognitive decline is essential for timely diagnosis and treatment. This study aimed to evaluate whether upper-limb movement dynamics derived from wrist-mounted inertial sensors during a fine motor task can accurately differentiate among heal…
  pubmed Pacheco-Santiago G, González-Aparicio II, Domínguez-Vega ZT, Velázquez-Álvarez L 等 2026 Jul 22 置信度 0.82
• Cross-task, explainable and real-time decoding of human emotion states by integrating gray and white matter intracranial neural activity.
  Decoding human emotion states from intracranial neural activity is key in developing affective brain-computer interfaces and new therapies for affective disorders. However, real-world application of decoding requires high performance that integrates neural act…
  pubmed Yang Y, Chen W, Chen Y, Ding L 等 2026 Jul 22 置信度 0.82
• ANGPTL4 in gestational diabetes: a diagnostic biomarker linked to placental senescence.
  Current diagnostic methods for Gestational Diabetes Mellitus (GDM) inadequately reflect early placental pathophysiology. Accelerated cellular senescence in trophoblasts has been reported as a pathological feature associated with the GDM placenta. However, the …
  pubmed He YF, Chen H, Zhang CM, Yang SS 等 2026 Jul 23 置信度 0.82
• [Medical prior-guided TabMap deep learning model for ovarian cancer prediction and interpretability analysis].
  To develop a TabMap image mapping and deep learning prediction framework that integrates medical prior knowledge to address the challenges of complex feature associations in tabular medical data and insufficient model interpretability in early ovarian cancer d…
  pubmed Zhu J, Tan S, Huang F, Cai G 等 2026 Jul 20 置信度 0.82
• [Interpretable machine learning models for preoperative precision prediction of perineural invasion in cervical cancer to support treatment decision: a multicenter retrospective study].
  To develop an interpretable machine learning model and web-based prediction tool for preoperative risk assessment of perineural invasion (PNI) in cervical cancer.
  pubmed Zhu M, Liu X, Zhao S, Zhang X 等 2026 Jul 20 置信度 0.82
• Deep Learning-Driven Anticancer Drug Discovery: Emodepside as a Potential Therapeutic Candidate for Triple-Negative Breast Cancer.
  Triple-negative breast cancer (TNBC) is an aggressive breast cancer subtype with a poor prognosis. The absence of effective targeted therapies and endocrine treatment options leads to limited therapeutic options, which remains one of the major clinical challen…
  pubmed Xu Y, Dong T, Li B, Yu J 等 2026 Aug 10 置信度 0.82
• Dynamic Aware Biopsy Needle Identification in Ultrasound Images Using Temporal Prior Guided U-Net Cross Transformer With Limited Training Data.
  Ultrasound-guided needle placement has been commonly used for minimally invasive clinical procedures, including biopsy, regional anesthesia and localized drug administration. This study aimed to enhance existing deep learning frameworks by incorporating a clas…
  pubmed Lee M, Beom DG, Bae EH, Kim SW 等 2026 Oct 置信度 0.82
• A multimodal machine learning model integrating plasma biomarkers and MRI metrics for non-invasive prediction of amyloid-β pathology in mild cognitive impairment.
  BackgroundAccurate, non-invasive prediction of cerebral amyloid-β (Aβ) pathology in mild cognitive impairment (MCI) remains challenging yet critical for early intervention.ObjectiveTo develop a multimodal machine learning model integrating clinical…
  pubmed Fang Q, Guo Y, Chen L, Li Y 等 2026 Jul 22 置信度 0.82
• Post-thrombectomy models for outcome prediction in ischemic stroke: systematic review and external validation.
  Outcome prediction models for patients with ischemic stroke after endovascular thrombectomy (EVT) demonstrated the value of including post-procedural predictors. We systematically reviewed and externally validated models that incorporated post-procedural predi…
  pubmed Li X, Alexandrov N, Veltman Y, van Walsum T 等 2026 Jul 22 置信度 0.82
• Artificial intelligence in microbiome data analysis: Applications in head and neck cancer.
  This chapter reviews AI-driven approaches, including machine learning and deep learning, for analyzing microbiome data in head and neck cancer (HNC). It highlights the role of artificial intelligence in identifying microbial biomarkers, predicting treatment ou…
  pubmed Kurt B, Babalola AE, Chaurasia A 2026 置信度 0.82
• Physicochemical fingerprinting reveals convergent evolutionary determinants of enterovirus A71 neurovirulence through integrative machine learning and structural analysis.
  Enterovirus A71 (EV-A71) causes hand, foot, and mouth disease and can trigger life-threatening neurological complications, yet the sequence-level physicochemical correlates of CNS involvement across globally circulating lineages remain incompletely defined. He…
  pubmed Wang X, Li F 2026 Sep 置信度 0.82
• Multi-omics and artificial intelligence nominate PCLAF as a prognostic and druggable target for hepatitis B virus-associated hepatocellular carcinoma.
  PCLAF (PCNA clamp-associated factor) is a protein involved in DNA replication and DNA repair. Aberrant PCLAF expression has been reported in multiple malignancies and is associated with tumor progression and poor clinical outcomes. However, the biological role…
  pubmed Shu F, Chen Y, Yang X, Gou G 等 2026 Nov 置信度 0.82
• Understanding the hippocampus as an apex of the cortical hierarchy and self-supervised predictive learning engine.
  The mammalian cortex is organized along hierarchical gradients that extend from primary sensory regions to transmodal association networks. Converging neuroanatomical theory and data-driven analyses place the hippocampus at the apex of this hierarchy, where it…
  pubmed DeKraker J, Eichert N, Hong SJ, Evans AC 等 2026 Oct 置信度 0.82
• Automated acute pain assessment in brachycephalic cats with ocular pain using the Feline Grimace Scale.
  This study aimed to evaluate the feasibility and limitations of an AI-powered Feline Grimace Scale (FGS) pipeline for acute pain assessment in brachycephalic cats with ocular pain.
  pubmed Steagall PV, Li J, Marangoni S, Bukhari SSUH 2026 Jul 22 置信度 0.82
• Alzheimer's disease risk prediction via perceptual deformable attention generative adversarial network with large foundation models.
  Predicting the risk of Alzheimer's disease (AD) is fundamental for early-stage intervention. Nevertheless, most methods struggle to extract multi-omics associative patterns due to the limited feature perception and inflexible disease modeling. This paper propo…
  pubmed Xing Z, Liu Z, Zhang DF, Xie K 等 2026 Sep 置信度 0.82
• Forecasting and real-time detection of neonatal seizures: A machine learning perspective.
  Recognition and treatment of neonatal seizures, primarily diagnosed using EEG, are essential to protect the developing brain, yet only 11% of seizures are treated within 1 hour of onset. Developing seizure forecasting and detection systems could help address t…
  pubmed Skoric T, Djermanovic M, O'Toole JM, De Vos M 等 2026 Oct 置信度 0.82
• Non-invasive differentiation between aplastic anemia and myelodysplastic syndromes based on an 8-feature lightGBM model: A multicenter external validation study.
  Given the highly overlapping pancytopenic phenotypes, non-invasive differentiation between aplastic anemia (AA) and myelodysplastic syndromes (MDS) remains a formidable clinical challenge. The current diagnostic gold standard relies on invasive bone marrow bio…
  pubmed Wang S, Cai Z, Wei W, Zhang S 等 2026 Jul 16 置信度 0.82
• Reply to the letter to the editor: "Machine learning model for predicting preeclampsia-related adverse outcomes".
  We thank Liu et al. for their constructive comments on our article reporting the internal and external validation of a reduced-feature machine learning model for the prediction of preeclampsia-related adverse outcomes. The letter raises four points, which we a…
  pubmed Hackelöer M, Rana S, Verlohren S 2026 Jul 22 置信度 0.82
• Centrosome-related gene SPHK1 drives bladder cancer progression and therapeutic vulnerability.
  Centrosome-related genes (CRGs) regulate cell division and genomic stability and may influence tumor progression, but their prognostic and functional roles in bladder cancer (BLCA) are not fully defined.
  pubmed Dong C, Fang Z, Han Y, Yin Y 等 2026 Sep 置信度 0.82
• AI-ECG Risk Stratification for Atrial Fibrillation: Real-World Performance and Explainability.
  Artificial intelligence-enabled electrocardiography (AI-ECG) has emerged as a potential method for identifying atrial fibrillation (AF) from sinus rhythm. However, its clinical utility and interpretability in routine practice remain uncertain.
  pubmed Matsuo K, Sobue Y, Miyake T, Takeda K 等 2026 Aug 置信度 0.82
• Lung ultrasound interpretation using deep learning for the detection of B-lines in dogs.
  Deep learning (DL) shows promise for interpretation of lung ultrasound (LUS) images in humans, but its performance in animals remains underexplored.
  pubmed Ward JL, VanBerlo B, Huggard B, Smith D 等 2026 Jul 1 置信度 0.82
• First, Do NoHarm: How Pharmaceutical AI Is Improving Care Across Brazil.
  Medication errors are a persistent challenge in health care across the world. In this News and Perspectives article, JMIR Correspondent Luke Taylor reports on NoHarm, a nonprofit AI tool changing pharmacy in Brazil, and its potential to relieve burden and impr…
  pubmed Taylor L 2026 Jul 22 置信度 0.82
• MoESurv: a zero-sample and transferable survival prediction framework for rare cancers using mixture of experts.
  Accurate survival prediction is crucial for personalized cancer treatment but remains challenging for rare cancers due to limited data. Most deep learning models require large training datasets, which are unavailable for rare cancer types, creating a significa…
  pubmed Fang S, Wang Y, Zhou M, Shao Y 等 2026 Aug 3 置信度 0.82
• Label-free SERS for the detection of renal failure biomarkers in blood serum using gold nanoparticles as a substrate.
  Renal failure (RF) requires rapid and accurate diagnosis to improve patient outcomes and quality of life. Conventional diagnostic methods are often invasive and time-consuming, highlighting the need for sensitive analytical approaches.
  pubmed Sarfraz F, Naeem M, Irfan Majeed M, Nawaz H 等 2026 Jul 置信度 0.82
• Utilizing machine learning to identify multimodal signatures for patients who would benefit from the addition of tremelimumab to durvalumab and chemotherapy (TRIDENT).
  POSEIDON (NCT03164616) was a randomized, open-label, multicenter phase 3 trial comparing first-line durvalumab with or without tremelimumab in combination with chemotherapy versus chemotherapy alone in patients with metastatic non-small-cell lung cancer (NSCLC…
  pubmed Skoulidis F, Jabbour SK, Garon EB, Iyengar P 等 2026 Jul 22 置信度 0.82
• Comprehensive Characterization of Clinical Phenotypes and CTG Repeat-Associated Manifestations in Spinocerebellar Ataxia Type 8.
  Spinocerebellar ataxia type 8 (SCA8) is traditionally characterized as a cerebellar syndrome, yet emerging evidence suggests significant phenotypic heterogeneity. The complex non-linear relationship between genetic burden and clinical severity remains understu…
  pubmed Yang D, Tang C, Zhan Y, Yang L 等 2026 Jul 22 置信度 0.82
• When Does Hyperparameter Optimization Matter in Imbalanced Medical Classification? A Systematic Benchmark Study Across Cost Asymmetry and Imbalance Conditions
  Class imbalance and asymmetric misclassification costs are pervasive in medical machine learning, yet their joint interaction with hyperparameter optimization (HPO) method selection remains largely uncharacterized. We present the first systematic benchmark stu…
  datacite Cengiz, Mehmet Ali, Adigüzel, Meryem, Öztürk, Zeynep 2026 置信度 0.66
• When Does Hyperparameter Optimization Matter in Imbalanced Medical Classification? A Systematic Benchmark Study Across Cost Asymmetry and Imbalance Conditions
  Class imbalance and asymmetric misclassification costs are pervasive in medical machine learning, yet their joint interaction with hyperparameter optimization (HPO) method selection remains largely uncharacterized. We present the first systematic benchmark stu…
  datacite Cengiz, Mehmet Ali, Adigüzel, Meryem, Öztürk, Zeynep 2026 置信度 0.66
• Explainable AI for Healthcare Decision Support
  Explainable AI for Healthcare Decision Support This article examines the growing role of Explainable Artificial Intelligence (XAI) in improving transparency, trust, and accountability within healthcare decision support systems. As artificial intelligence becom…
  datacite Uchechukwu, Ephraim Buzugbe 2025 置信度 0.66 Explainable Artificial Intelligence (XAI)Clinical Decision Support Systems (CDSS)Machine LearningTrustworthy AISHAP