Gastroenterology

CAD-SEL: A dual-modal colonoscopy dataset of subepithelial lesion.

Subepithelial lesions (SELs) of the gastrointestinal tract encompass a heterogeneous spectrum of histology, ranging from benign to malignant. Their detection during colonoscopy is critical yet challenging, as endoscopic interpretation is highly operator-dependent with variable diagnostic performance. Artificial intelligence (AI) offers great promise for assisting endoscopists in SEL detection and ...

From Genomic Instability to Epigenetic Signatures: The Evolving Landscape of Circulating Cell-free DNA in Metabolic Dysfunction-Associated Steatotic Liver Disease.

Metabolic dysfunction-associated steatotic liver disease (MASLD) represents a leading global health burden, yet its diagnosis and staging rely heavily on invasive liver biopsies. Liquid biopsy, utilizing circulating cell-free DNA (cfDNA), offers a promising noninvasive alternative to capture hepatic genomic instability. This review consolidates current knowledge on cfDNA biomarkers in MASLD, movin...

Impact of a real-time automatic quality control system for magnetically controlled capsule gastroscopy: a multicenter randomized controlled trial.

BACKGROUND: Quality control can reduce variations in operators' performance conducting magnetically controlled capsule gastroscopy (MCCG). However, an...

Medicinal Plants and the Gastrointestinal Microbiota in Chronic Diseases Modulation: A Structured Mechanistic and Translational Review.

The gut microbiome supports digestion, immunity, and metabolism; its imbalance (dysbiosis) drives inflammation and metabolic dysfunction, contributing...

Interpretable LightGBM model for predicting postoperative gastrointestinal hemorrhage in elderly hip fracture patients: leveraging systemic inflammation and medication exposures for personalized risk stratification.

BACKGROUND: Postoperative gastrointestinal (GI) bleeding is a serious complication after hip fracture surgery in older adults, yet perioperative risk ...

AI-Driven Hemodynamic Detection of Self-Induced Daydreaming With EMG-Based Physiological Triggers During Pre- and Post-Prandial States Using fNIRS and EGG.

BACKGROUND: Daydreaming can be monitored either to avoid it while doing hands-on tasks or to enhance it to foster creativity. Although significant res...

Predicting Prognosis for Gastric Cancer Patients Receiving Neoadjuvant Treatment With Body Composition-Based Deep Learning.

BACKGROUND: This study sought to develop an innovative body composition (BC)-based deep learning (DL) model to precisely evaluate survival in gastric ...

Development and validation of a machine learning model and a web tool for predicting the risk of Crohn's disease diagnosis in Chinese patients.

OBJECTIVES: Diagnostic delay in Crohn's disease (CD) may increase the risk of poor prognosis. This study developed and validated a machine learning (M...

Noninvasive Screening for High-Risk Esophageal Varices in Cirrhosis: Current and Emerging Methods.

The primary goal of variceal screening in patients with cirrhosis is to identify high-risk esophageal varices (HREV) and implement preventative measur...

Impact of Artificial Intelligence-Assisted Endoscopy on Screening for Upper Gastrointestinal Cancer in a Large-Scale Health Screening Facility.

OBJECTIVES: Artificial intelligence (AI)-assisted endoscopy has been developed for the early detection of upper gastrointestinal cancer; however, its ...

Personalized assessment of hyperuricemia probability in metabolic dysfunction-associated steatotic liver disease: construction and multicenter validation of a clinical nomogram.

BACKGROUND: Metabolic dysfunction-associated steatotic liver disease is increasingly recognized as a precursor to secondary hyperuricemia, significant...

IN-HUMAN FEASIBILITY AND SAFETY OF SUBRETINAL DRUG INJECTION THROUGH ATTACHED RETINA USING A ROBOTIC COMANIPULATION SYSTEM.

PURPOSE: To evaluate feasibility and safety of robot-assisted subretinal injections through attached retina using the comanipulated Mynutia system in ...

Noninvasive Tests for Predicting Decompensation in Compensated Advanced Chronic Liver Disease: A Comprehensive Review.

Strong non-invasive tests (NITs) are needed to predict decompensation in patients with compensated advanced chronic liver disease (cACLD) and improve ...

Identification of Hepatic Fibrosis and Steatosis via A Point-of-Care Transient Elastography System With Integrated AI.

BACKGROUND & AIMS: Transient elastography (TE) is routinely undertaken for non-invasive assessment of liver fibrosis and steatosis, but is limited by ...

The role of artificial intelligence in colonoscopy performance and quality among gastroenterology fellows.

The Prognostic and Biological Value of PGF-Based H&E Pathomics in Hepatocellular Carcinoma.

PURPOSE: Placental growth factor (PGF) is associated with the progression of hepatocellular carcinoma (HCC), but current research on this relationship...

Deep Learning Model Based on Tumor and Visceral Adipose Tissue CT Features for Predicting Peritoneal Metastasis Risk after Radical Gastrectomy in Serosa-Invasive Gastric Cancer.

Purpose To develop and validate a deep learning model integrating tumor and visceral adipose tissue (VAT) CT scan features with clinical indicators to...

[Dynamic assessment of upper airway in obstructive sleep apnea patients with a focus on drug-induced sleep endoscopy].

The key pathophysiological feature of obstructive sleep apnea（OSA） is dynamic collapse of the upper airway during sleep. Polysomnography（PSG） and awak...

Integration Analysis of Bayesian and Machine Learning for Heterogeneity, Biomarkers, and Optimal Combination Regimens of Pucotenlimab in Solid Tumors.

The efficacy of PD-1 inhibitor pucotenlimab (HX008) in solid tumors exhibits heterogeneity. This study integrated data from 6 clinical trials (coverin...

Deep Learning-Based Prediction System for Surgical Difficulty in Rectal Cancer Patients Using MRI Pelvimetry.

PURPOSE: This study presents a system that automatically predicts the difficulty of laparoscopic total mesorectal excision (TME) using magnetic resona...