GERD

Evaluating Conversational Image Segmentation for Medicine: Performance, Failure Modes, and a Fairness Audit Across Seven Modalities

Medical-image segmentation underpins quantitative diagnostics and research, yet state-of-the-art models remain task-specific and data-hungry. The recent emergence of powerful, multimodal large language models (LLMs) presents a generalizable option; however, their efficacy in the specialized medical domain remains largely unquantified. We aim to benchmark the foundational Gemini 2.5 Flash and Gemin...

Evaluation of Large Language Models in the Clinical Management of Patients With Upper Gastrointestinal Bleeding : Insights From Real-World Patient Data

Upper gastrointestinal bleeding (UGIB) is a life-threatening emergency requiring rapid risk assessment. Current scoring tools have limited accuracy. Large language models (LLMs) may support clinical decision-making, but their role in UGIB management is unclear. This study evaluated LLMs for patient risk classification, prediction of endoscopic findings, and alignment with routine clinical decision...

Artificial Intelligence for Significant Mitral Regurgitation Screening and Diagnosis: A Systematic Review and Meta-analysis

To evaluate performance of artificial intelligence (AI) models using electrocardiogram (ECG) and echocardiogram (ECHO) for predicting significant mitr...

Scaling genetic discovery for organ volumes using machine learning-assisted imputation and bias-corrected GWAS

MRI-derived organ and tissue volumes are powerful endophenotypes for studying complex disease, but their availability is limited by cost and throughpu...

A Zero-Burden Sleep Foundation Model Built on Cardiorespiratory Signals from 800,000+ Hours of Multi-Ethnic Sleep Recordings

Sleep disorders pose a major global health burden and are associated with a wide range of adverse health outcomes. Polysomnography (PSG) is the gold s...

Artificial Intelligence Significantly Improves Adenoma Detection Rate but Does Not Affect Polyp Detection Rate in Colonoscopy: A Propensity Score Matching Study

Colorectal cancer (CRC) remains a major cause of cancer-related morbidity and mortality worldwide. Endoscopy and adenoma removal are effective in redu...

Reliability of Artificial Intelligence-enhanced Electrocardiography

The scientific literature on artificial intelligence-enabled electrocardiography (AI-ECG) has defined a robust performance of AI models in detecting a...

Integrating Protein-protein Interaction Networks and Machine Learning to Identify Biomarkers of Cancer Onset

Recent large-scale plasma proteomic studies have identified a set of biomarkers for the diagnosis of early cancer onset, but the predictive performanc...

The Association Between Oral Microbiota and Chronic Obstructive Pulmonary Disease: An Integrated Study of Genetic Causal Inference and Bioinformatics Analysis

Chronic obstructive pulmonary disease (COPD) is the third leading cause of global mortality. Emerging evidence suggests the oral microbiome may contri...

Research on the Diagnostic Value and Immune Microenvironment Regulatory Mechanism of FOLR3 Gene in Endometrial Cancer Based on Multi-omics Data Algorithms

FOLR3 serves as an important member of the folate metabolic pathway and plays a crucial role in various malignant tumors. However, the expression patt...

Identification of hub immune-related genes and construction of predictive models for systemic lupus erythematosus by bioinformatics combined with machine learning.

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease that involves multiple systems. SLE is characterized by the production of autoantib...

Deciphering mitochondrial dysfunction in keratoconus: Insights into ACSL4 from machine learning-based bulk and single-cell transcriptome analyses and experimental validation.

Keratoconus (KC) is a prevalent ectatic corneal disease and the leading cause of corneal transplantation globally. Despite evidence of mitochondrial a...

Pilot evaluation of a novel, automated ergonomics assessment tool.

BACKGROUND AND STUDY AIMS: Gastroenterologists are prone to endoscopy-related musculoskeletal injuries (ERI). Current interventions lack real-time mon...

Development and Validation of a Multi-Task Artificial Intelligence-Assisted System for Small Bowel Capsule Endoscopy.

OBJECTIVE: To develop a multi-task artificial intelligence-assisted system for small bowel capsule endoscopy (SBCE) based on various Transformer neura...

Identification of biomarkers associated with inflammatory response in Parkinson's disease by bioinformatics and machine learning.

Parkinson's disease (PD) is a common and debilitating neurodegenerative disorder. The inflammatory response is essential in the pathogenesis and progr...

Artificial Intelligence in Endoscopy for Predicting Helicobacter pylori Infection: A Systematic Review and Meta-Analysis.

PURPOSE: This meta-analysis aimed to assess the diagnostic performance of artificial intelligence (AI) based on endoscopy for detecting Helicobacter p...

Identification and Immunological Characterization of Cuproptosis Related Genes in Preeclampsia Using Bioinformatics Analysis and Machine Learning.

Preeclampsia (PE) is a pregnancy-specific disorder characterized by an unclearly understood pathogenesis and poses a great threat to maternal and feta...

Improved in Silico Identification of Protein-Protein Interactions Using Deep Learning Approach.

Protein-protein interactions (PPIs) perform significant functions in many biological activities likewise gene regulation, metabolic pathways and signa...

Image detection method for multi-category lesions in wireless capsule endoscopy based on deep learning models.

BACKGROUND: Wireless capsule endoscopy (WCE) has become an important noninvasive and portable tool for diagnosing digestive tract diseases and has bee...

Transformer-Based Wireless Capsule Endoscopy Bleeding Tissue Detection and Classification

Informed by the success of the transformer model in various computer vision tasks, we design an end-to-end trainable model for the automatic detecti...