Gastroenterology

Trajectory-Informed Breathomics for Dynamic Mapping of Health and Disease: Toward a Health Navigation Framework

Most diagnostic frameworks treat disease as static, overlooking its inherently dynamic and continuous progression. Noninvasive biomarkers capable of capturing physiological trajectories are critically needed for proactive health management. We developed a breath-based health navigation framework using exhaled volatile organic compounds (VOCs) as integrative, real-time indicators of systemic metabo...

Interpretable machine learning applied to high-dimensional salivary proteomics accurately classifies pediatric inflammatory bowel diseases

Inflammatory bowel diseases (IBD), including Crohn’s disease (CD), ulcerative colitis (UC), and IBD-unclassified (IBD-U), are chronic inflammatory disorders of the gastrointestinal tract. Current methods for classification and longitudinal monitoring are invasive, expensive, and often delayed, limiting timely diagnosis and management. This study reports the first application of high-dimensional sa...

Morphological and Functional Alterations in Type 2 Diabetes Pancreata assessed with MRI-based metrics and [18F]FP-(+)-DTBZ PET

To determine if combining PET-derived beta-cell mass (BCM) estimates with MRI- based morphology metrics improves the prediction of beta-cell functiona...

Multimodal AI for Precision Preventive Cardiology

Coronary artery disease (CAD) is the leading cause of death worldwide, yet it is highly preventable. Early detection is critical, particularly because...

BASIC: Bayesian Spiral Attention Classifier for Interpretable Medical Image Classification

Accurate medical image classification is critical for early diagnosis and effective treatment planning. However, conventional deep learning models oft...

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 complex, multifactorial nature of IBS pain leads t...

AI-Powered Radiotherapy for Resource-Limited Settings: Advancing Cervical and Prostate Cancer Treatment Planning with the Radiation Planning Assistant (RPA)

Radiotherapy treatment planning is a resource-intensive process characterized by multiple manual steps and clinical hand-offs that contribute to treat...

Hemi-brain growth as a biomarker for whole brain growth

Accurate cerebrospinal fluid (CSF) and brain volume estimation are important components for evaluating hydrocephalus treatments, including shunts and ...

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 rece...

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. L...

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 symptoms, resulting in one of the highest cancer morta...

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 interest for early detection of hepatocellular carcinom...

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...

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 colonoscopy remains the gold standard for early detect...

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 timely intervention and improved outcomes. Artificial i...

Predicting Alzheimer’s Disease Diagnosis, a Decade or more Years before Onset using the Electronic Health Record and Random Forest Machine Learning Models

There is need to detect and intervene in pre-clinical phases of Alzheimer’s disease (AD). Electronic health records (EHRs) may help predict AD using m...

CLINES: Clinical LLM-based Information Extraction and Structuring Agent

Clinical narratives in electronic health records (EHRs) contain essential diagnostic, therapeutic, and temporal information that is often missing from...

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 are directed at single anatomical sites and inadequ...