Gastroenterology

Inflammatory Bowel Disease

Latest AI and machine learning research in inflammatory bowel disease for healthcare professionals.

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Clinically-Grounded Counterfactual Reasoning for Medical Video Diagnosis

Medical video diagnosis involves inferring clinical decisions from dynamic tissue responses througho...

Performance of IBD machine learning classifiers varies across microbiome training data independent of geographic diversity

Microbiome-based machine learning classifiers show increasing promise for disease identification acr...

SurgLQA: Scalable Long-Horizon Surgical Video Question Answering

Surgical Video Question Answering (VideoQA) provides a promising paradigm for dynamic intraoperative...

Genetic code expansion enables programmable covalent protein design

Covalent chemistry has transformed small-molecule drug discovery, yet analogous strategies for prote...

Contrastive Learning under Noisy Temporal Self-Supervision for Colonoscopy Videos

Learning robust representations of polyp tracklets is key to enabling multiple AI-assisted colonosco...

Multi-LLM Disagreement as a Scalable Detector of Human Annotation Errors in Structured Data from Clinical Free-Text

Abstract Objective: Structured extraction from clinical free-text depends on human annotators whose ...

immuneKG: An Immune-Cell-Aware Knowledge Graph Framework for Target Discovery in Immune-Mediated Diseases

Biomedical knowledge graphs have emerged as foundational infrastructure for AI-driven drug discovery...

Disrupted oral microbial networks and reproducible community signatures implicate the oral-gut axis in Crohn's disease

Background: Emerging evidence suggests that the oral microbiome may contribute to aberrant gut immun...

DepthPilot: From Controllability to Interpretability in Colonoscopy Video Generation

Controllable medical video generation has achieved remarkable progress, but it still lacks interpret...

Dissecting clinical reasoning failures in frontier artificial intelligence using 10,000 synthetic cases

Background: Current medical large language model (LLM) evaluations largely rely on small collections...

ASGNet: Adaptive Spectrum Guidance Network for Automatic Polyp Segmentation

Early identification and removal of polyps can reduce the risk of developing colorectal cancer. Howe...

Representation geometry shapes task performance in vision-language modeling for CT enterography

Computed tomography (CT) enterography is a primary imaging modality for assessing inflammatory bowel...

A structure-informed deep learning framework for modeling TCR-peptide-HLA interactions

The interaction between T cell receptors (TCRs), peptides, and human leukocyte antigens (HLAs) under...

Colon-Bench: An Agentic Workflow for Scalable Dense Lesion Annotation in Full-Procedure Colonoscopy Videos

Early screening via colonoscopy is critical for colon cancer prevention, yet developing robust AI sy...

Agentic Automation of BT-RADS Scoring: End-to-End Multi-Agent System for Standardized Brain Tumor Follow-up Assessment

The Brain Tumor Reporting and Data System (BT-RADS) standardizes post-treatment MRI response assessm...

Spectral Rectification for Parameter-Efficient Adaptation of Foundation Models in Colonoscopy Depth Estimation

Accurate monocular depth estimation is critical in colonoscopy for lesion localization and navigatio...

Association of Radiologic PPFE Change with Mortality in Lung Cancer Screening Cohorts

Background: Pleuroparenchymal fibroelastosis (PPFE) is an upper lobe predominant fibrotic lung abnor...

Deep Learning-based Differentiation of Drug-induced Liver Injury and Autoimmune Hepatitis: A Pathological and Computational Approach

Drug-induced liver injury (DILI) is an acute inflammatory liver disease caused not only by prescript...

BEGA-UNet: Boundary-Explicit Guided Attention U-Net with Multi-Scale Feature Aggregation for Colonoscopic Polyp Segmentation

Accurate polyp segmentation from colonoscopy images is critical for colorectal cancer prevention, ye...

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