Gastroenterology

Machine learning-based risk modeling for safety-focused learning curve assessment in robotic left-sided colorectal cancer surgery.

The transition from laparoscopic to robotic surgery for left-sided colorectal cancer raises safety c...

Hybrid imaging-clinical model for predicting microvascular invasion in hepatocellular carcinoma using deep learning-derived features from CT.

The role of adipose tissue in predicting microvascular invasion (MVI) in patients with hepatocellula...

Development and Validation of a Urinary Exosomal miRNA Diagnostic Panel for Early Detection of Esophageal Cancer.

Esophageal squamous cell carcinoma (ESCC) remains a leading cause of cancer-related mortality, with ...

Multiparametric MRI radiomics nomogram predicts synchronous distant metastasis in rectal cancer.

This study aimed to evaluate the utility of a multiparametric MRI-based radiomics nomogram for ident...

Compact deep learning models for colon histopathology focusing performance and generalization challenges.

Semi-Supervised Fatty Liver Classification Using Attention-Based Graph Neural Network Models.

BACKGROUND: Fatty liver disease is a common condition linked to metabolic syndrome, cardiovascular d...

Artificial intelligence in gastrointestinal endoscopy: a global clinical trial analysis.

Interpretable machine learning model for predicting in-hospital mortality in elderly acute pancreatitis: Development and validation in a multicenter cohort.

BACKGROUND: Elderly acute pancreatitis (AP) patients face significantly higher in-hospital all-cause...

Development and validation of an interpretable machine learning model for non-invasive screening of precancerous gastric lesions using symptom and lifestyle data: a multicentre cohort study.

BACKGROUND: Precancerous gastric lesions (PLGC) are a critical stage in gastric cancer progression, ...

Morphological characterization of a novel model of steatohepatitis in the FAH-/- pig.

Metabolic dysfunction-associated steatohepatitis (MASH) is a global health care burden. Appropriate ...

A prognostic signature of ferroptosis and lipid metabolism related genes predicts survival and immunotherapy response in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is a common and aggressive form of cancer. There is an in...

Intestinal transcriptomic analysis and prediction of biomarkers associated with mucosal healing following vedolizumab treatment in ulcerative colitis using machine learning.

Liver cancer risk stratification using deep learning on nationwide longitudinal health screening data: a retrospective cohort study.

BACKGROUND: Current liver cancer screening in Korea focuses on viral hepatitis or cirrhosis, despite...

Learning the anatomical topology consistency driven by Wasserstein distance for weakly supervised 3D pancreas registration in multi-phase CT images.

Accurate and automatic registration of the pancreas between contrast-enhanced CT (CECT) and non-cont...

Correction in: Artificial Intelligence-Assisted Capsule Endoscopy Versus Conventional Capsule Endoscopy for Detection of Small Bowel Lesions: A Systematic Review and Meta-Analysis.

Integrating multi-omics and machine learning systematically deciphers cellular heterogeneity and fibrotic regulatory networks in the progression from MASLD to MASH.

The progression from metabolic dysfunction-associated steatotic liver disease (MASLD) to metabolic d...

Survival and Surrogate Biomarkers in Interventional Oncology Trials: Pitfalls, Challenges, and Future Directions.

INTRODUCTION: Interventional oncology (IO) is a key component of multidisciplinary cancer care, deli...

An interpretable machine learning model for prediction of significant liver fibrosis in comorbid chronic hepatitis B and nonalcoholic fatty liver disease: a retrospective development and validation study.

Morphological subphenotypes of acute pancreatitis-related acute respiratory distress syndrome.

Deep Learning Analysis Based on Dual-energy CT-Derived Iodine Map for Predicting PD-L1 Expression in Gastric Cancer: A Multicenter Study.

RATIONALE AND OBJECTIVES: PD-L1 expression is a critical biomarker in guiding immunotherapy for gast...

Computer Aided Polyp Detection Multi-center International Randomized Controlled Study with a Focus on Community Clinics: GAIN Clinical Trial.

BACKGROUND/AIMS: Computer-aided polyp detection (CADe) systems can enhance polyp detection, although...