Gastroenterology

CT-based multiple instance and ensemble learning for lymph node metastasis prediction in esophageal squamous cell carcinoma: a multicentre, retrospective study.

Long-Term Follow-Up in Liver Transplantation and Combined Cardiac Surgery: Validation and Refinement of the LT+CS Risk Score Using Advanced Machine Learning.

BACKGROUND: Combined liver transplantation (LT) and cardiac surgery (LT+CS) is a therapeutic option for patients with end-stage liver disease (ESLD) and severe cardiac dysfunction. Despite its potential, evidence on long-term outcomes and prognostic factors remains limited. STUDY DESIGN: Forty-six patients underwent single-staged LT+CS (2005 to 2023) and had a minimum 1-year follow-up. Univariate ...

Explainability-informed benchmarking of two deep learning models for organ-at-risk segmentation in MR-guided adaptive radiotherapy.

INTRODUCTION/BACKGROUND: Segmentation of gastrointestinal (GI) organs-at-risk (OARs) is a critical yet time-consuming step in MR-guided adaptive radio...

Automating classification of treatment responses to combined targeted therapy and immunotherapy in HCC.

Tyrosine kinase inhibitor (TKI) combined with immunotherapy regimens are now widely used for treating advanced hepatocellular carcinoma (HCC), but the...

Potential mechanisms of Si-Wu-Tang against esophageal squamous cell carcinoma: A machine learning pharmacological study.

The purpose of this study is to explore the potential mechanism of Si-Wu-Tang (SWT) against esophageal squamous cell carcinoma (ESCC). Initially, 18 a...

Generative artificial intelligence for patient education material on gastric cancer prevention.

BACKGROUND:  This study assessed the effectiveness of large language models (LLMs) in generating lay summaries for patient education on the management...

Hydrogel-enabled drug delivery for ulcerative colitis.

Ulcerative colitis (UC) represents a chronic, relapsing inflammatory condition primarily affecting the colonic and rectal mucosa, presenting substanti...

Predicting vesicoureteral reflux outcomes using artificial intelligence: A critical appraisal using APPRAISE-AI.

Vesicoureteral reflux (VUR) is a common congenital urinary tract anomaly in children, associated with recurrent urinary tract infections (UTIs) and lo...

The association between liver disease and stroke risk: A cross-sectional study with machine learning in a large-scale Chinese cohort.

INTRODUCTION: This study aimed to investigate the association between liver disease (LD) and stroke using cross-sectional data from the China Health a...

Development of retrieval-augmented generation-based large language model for drug-induced liver injury using Livertox data.

BACKGROUND: Idiosyncratic DILI is a complex clinical challenge requiring timely and accurate decision support. LiverTox, curated by the National Insti...

Omic analysis of the protein profile in digestive tumours, from proteomics to clinical practice.

Proteomics has emerged as a key tool in precision medicine, enabling in-depth molecular characterization of digestive tumours. This article outlines a...

Prediction model for ctDNA detectability in liquid comprehensive genomic profiling of advanced pancreatic cancer based on Japanese real-world data.

BACKGROUND: Circulating tumor DNA (ctDNA) is sometimes undetectable in liquid comprehensive genomic profiling (CGP) of advanced-stage pancreatic cance...

The use of advanced machine learning to predict outcomes after atezolizumab plus bevacizumab for advanced hepatocellular carcinoma: a retrospective cohort study.

BACKGROUND: Combination immune checkpoint inhibitors are recommended as first-line therapy for advanced hepatocellular carcinoma. However, only a thir...

Drone-based geospatial prediction modeling identifies Fasciola hepatica infection risk in the Cusco Highlands of Peru.

BACKGROUND: Fascioliasis is a neglected infectious disease affecting agricultural communities worldwide, with the Peruvian Andes among the most severe...

Outcomes of Artificial Intelligence Enhanced Colonoscopy in a Tertiary Clinical Setting.

BACKGROUND AND AIMS: Colonoscopies reduce colorectal cancer incidence and mortality, but challenges remain in detecting all precancerous lesions. Oper...

Global research trends in robotic-assisted thoracoscopic surgery: a multidimensional analysis from 2000 to 2025.

OBJECTIVE: Robotic-assisted thoracoscopic surgery (RATS) has transformed thoracic surgery, yet fragmented research patterns obscure critical developme...

Evaluation of the Mayo endoscopic score in ulcerative colitis using a multimodal large language model: a human-blinded accuracy study.

BACKGROUND/AIMS: To date, some large language models (LLMs), such as Chat Generative Pre-trained Transformer 4-omni (ChatGPT-4o), can process images t...

The dynamics of hepatitis B virus transmission using a stochastic differential model and feed forward neural network approach.

Hepatitis B transmission is influenced by environmental variability, immune response and vaccination, making its spread inherently stochastic, while t...

Enhancing Inpatient Mortality Prognostication in Cirrhosis Patients Through Machine Learning Techniques.

Machine Learning in Cirrhosis: Moving From Static Admission Risk to Dynamic Decision Support.