Gastroenterology

Latest AI and machine learning research in gastroenterology for healthcare professionals.

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BASIC: Bayesian Spiral Attention Classifier for Interpretable Medical Image Classification

Accurate medical image classification is critical for early diagnosis and effective treatment planni...

Machine learning to phenotype pain and predict response to pain interventions among young adults with irritable bowel syndrome

Irritable bowel syndrome (IBS) is a prevalent disorder whose most debilitating symptom is pain. The ...

Hemi-brain growth as a biomarker for whole brain growth

Accurate cerebrospinal fluid (CSF) and brain volume estimation are important components for evaluati...

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 mod...

PANCDetect: Early Detection of Pancreatic Cancer from Multimodal EHR data with LLM Embeddings

Pancreatic cancer (PANC) is often diagnosed at late stages due to the absence of specific early symp...

Developing a Fully Automated Imaging Biomarker for HCC Risk Assessment via MRI-Based Tumor Segmentation and EPM

This study investigates the feasibility of using automated tumor segmentation as the region of inter...

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 t...

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 he...

Evaluating Large Language Models for Colonoscopy Preparation Assistance: Correctness and Diversity in Synthetic Dialogues

Colorectal cancer is the third leading cause of cancer-related deaths in the United States, and colo...

Continuous Multimodal AI with Wearable Vital Signs Predicts Postoperative Complications in the General Ward

Surgery is inherently associated with complications, making early detection the cornerstone of timel...

CLINES: Clinical LLM-based Information Extraction and Structuring Agent

Clinical narratives in electronic health records (EHRs) contain essential diagnostic, therapeutic, a...

Beyond Annotation: Leveraging Raw RNA-seq Reads via Foundation Models for Multi-Cancer Early Detection

Early cancer detection substantially improves patient survival, yet conventional screening methods a...

Clustering high-cost patients in England using machine learning: a population-based cohort study

To identify clusters of high-cost patients in England based on diagnoses and sociodemographic charac...

ML-Guided GWAS Reveals Genetic Architectures for MASLD for Overweight and Lean Individuals in the All of Us Cohort

Metabolic dysfunction-associated steatotic liver disease (MASLD) arises from excessive hepatic fat a...

Hepatic and abdominal adiposity in type 2 diabetes as assessed with machine learning on CT scans

The distribution of abdominal adipose depots and their mechanistic links to type 2 diabetes remain i...

Personalized Risk Stratification in Colon Cancer using Radiomic-Based Predictive Models

Colon Cancer (CC) is among the most frequently diagnosed malignancies and a leading cause of cancer-...

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