Gastroenterology

Comprehensive characterization of granular fibrotic and cellular features in liver tissue enabled by deep learning models

Histologic staging of metabolic dysfunction-associated steatohepatitis (MASH) requires semiquantitative assessment of hepatocellular ballooning, steatosis, lobular inflammation, and fibrosis. We hypothesize that quantitative histologic analysis will better reflect the continuous distribution of histologic features, and thus the disease biology. We developed an AI-powered digital pathology tool, Li...

Serum Exosomal Multi-Omic Signatures Stratify Glucose Tolerance in Cystic Fibrosis and Reveal Partial Therapeutic Reprogramming by CFTR Modulators

Cystic fibrosis-related diabetes (CFRD) affects up to 60% of adults with CF and contributes to poorer clinical outcomes, including accelerated lung decline and increased mortality. CFRD is often diagnosed late, with limited mechanistic insight and few tools for early detection. We profiled serum-derived exosomes from 186 individuals, 173 with CF, across two independent cohorts (Australia and Denma...

Beyond Accuracy: Multidimensional Evaluation of Large Language Models in Hepatocellular Carcinoma Management Emphasizing Prompting

Hepatocellular carcinoma is the most common type of primary liver cancer and remains a major global health challenge. In resource-limited settings, pa...

AI-based Hepatic Steatosis Detection and Integrated Hepatic Assessment from Cardiac CT Attenuation Scans Enhances All-cause Mortality Risk Stratification: A Multi-center Study

Hepatic steatosis (HS) is a common cardiometabolic risk factor frequently present but under-diagnosed in patients with suspected or known coronary art...

Predicting Short-Term Mortality in Severe Cirrhosis: An Interpretable Machine Learning Model Integrating Routine Clinical Indicators

The critical need for precise risk stratification in severe liver cirrhosis is underscored by its substantial 30-day mortality rates, demanding reliab...

Machine learning approach to dissect the clinical heterogeneity of IBD-associated fatigue

Extreme fatigue is a clinical symptom that affects >50% of individuals with Inflammatory Bowel Disease (IBD), with a similar prevalence across many co...

A Systematic Review of Multimodal Deep Learning and Machine Learning Fusion Techniques for Prostate Cancer Classification

Prostate cancer remains one of the most prevalent malignancies and a leading cause of cancer-related deaths among men worldwide. Despite advances in t...

Redefining ALS: Large-scale proteomic profiling reveals a prolonged pre-diagnostic phase with immune, muscular, metabolic, and brain involvement

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder with a largely unknown duration and pathophysiology of the pre-diagnostic ph...

An artificial intelligence-powered digital pathology platform to support large-scale deworming programs against soil-transmitted helminthiasis and intestinal schistosomiasis in resource-limited settings

The World Health Organization (WHO) has emphasised the need for innovative diagnostic tools to support the control and eliminate neglected tropical di...

Large Language Models Improve Cancer Survival Prediction Using Real-World Clinical Notes

In medical documentation, vast amounts of unstructured text are generated that are still underutilized in current prognostic models. We investigate th...

Diagnostic accuracy of Impedance Spectroscopy versus Digital Rectal Examination for Obstetric Anal Sphincter Injuries: a postpartum post-hoc analysis

Accurate diagnosis of obstetric anal sphincter injuries (OASIs) is critical for timely repair and prevention of long-term morbidity, yet digital recta...

Signal Mining and Analysis of Adverse Events of Isotretinoin: 20-year real-world pharmacovigilance analysis based on the FAERS database

To identify post-marketing adverse event (AE) signals associated with isotretinoin using real-world data from the U.S. Food and Drug Administration (F...

MetaMind: A Multi-Agent Transformer-Driven Framework for Automated Network Meta-Analyses

Network meta-analysis (NMA) enables simultaneous comparison of multiple interventions by integrating direct and indirect evidence from randomized cont...

Urinary pesticide profiles and liver disease risk in Thailand: a machine-learning risk-prediction model

Building on evidence linking urinary glyphosate to chronic liver disease (CLD) and hepatocellular carcinoma (HCC), we developed urinary pesticide prof...

Radiologist-AI Collaboration for Ischemia Diagnosis in Small Bowel Obstruction: Multicentric Development and External Validation of a Multimodal Deep Learning Model

To develop and externally validate a multimodal AI model for detecting ischaemia complicating small-bowel obstruction (SBO). We combined 3D CT data wi...

Altered microbial carbohydrate metabolism is associated with anxiety and gastrointestinal symptoms in patients with Generalized Anxiety Disorder

Generalized anxiety disorder (GAD) is a common psychiatric condition, with unknown etiology and pathophysiology. Recent studies have suggested alterat...

Revealing Shared Tumor Microenvironment Dynamics Related to Microsatellite Instability Across Different Cancers Using Cellular Social Network Analysis

Microsatellite instability (MSI) is a key biomarker for immunotherapy response and prognosis across multiple cancers, yet its identification from rout...

Bayesian machine learning enables discovery of risk factors for hepatosplenic multimorbidity related to schistosomiasis

One in 25 deaths worldwide is related to liver disease, and often with multiple hepatosplenic conditions. Yet, little is understood of the risk factor...

Diagnostic Performance of Self-Supervised Foundation Models for Intraoperative Quantification of Hepatic Macrovesicular Steatosis

Accurate intraoperative assessment of macrovesicular steatosis in donor liver biopsies is critical for transplantation decisions but is often limited ...

Entropy-Guided Sample-Specific Feature Selection for Robust Incomplete Multi-Omics Learning in Gut Microbiome Disease Prediction and Biomarker Discovery

The rapid advances in multi-omics data integration technologies have opened unprecedented avenues for dissecting the mechanisms and accelerating the c...