Gastroenterology

Interpretable fusion deep learning on super-resolution MRI for perineural invasion prediction in pancreatic ductal adenocarcinoma: a multicenter study.

PURPOSE: To develop an interpretable fusion deep learning model based on super-resolution (SR) MRI f...

Clinical practice, barriers to implementation, and priorities for equitable access of Stereotactic Body Radiation Therapy: An analysis of the global status by the ESTRO SBRT Focus Group.

BACKGROUND: Stereotactic Body Radiation Therapy (SBRT) has become an established treatment for sever...

Synergistic impact of insulin resistance and hepatic fibrosis on cardiovascular events in patients with coronary artery disease: A machine learning subtyping and interaction analysis.

BACKGROUND AND AIMS: Insulin resistance (IR) and hepatic fibrosis are significant yet underexplored ...

Real-world evidence in metabolic dysfunction-associated steatotic liver disease (MASLD): insights, challenges, and future directions.

Real-world evidence (RWE), derived from real-world data, offers key insights into metabolic dysfunct...

Emerging nanoparticle-based therapies for pancreatic cancer: Current clinical landscape.

Pancreatic cancer, particularly ductal adenocarcinoma (PDAC) is one of the most aggressive and letha...

Toxicophore-informed machine learning integrating Tox21 assay readouts for organ system-specific carcinogenicity prediction.

Accurate identification of carcinogenic hazards is essential for public health protection, yet tradi...

Revolutionizing Liver Imaging: Artificial Intelligence-Driven Advances in Diagnostics and Staging.

Artificial intelligence (AI) has emerged as a transformative tool in liver imaging, offering enhance...

Unified NDMI for small intestinal cine MRI: repeatability and sensitivity to multicenter variability.

PURPOSE: To establish a comparability-first cine-MRI paradigm for small intestinal motility using a ...

MethylMSI: Prediction of microsatellite instability based on DNA methylation profile and SVM model.

Microsatellite instability (MSI) has gained increasing attention as a promising biomarker for cancer...

A Simple Laboratory-based Machine Learning Model Accurately Predicts Advanced Liver Fibrosis in Metabolic Dysfunction-associated Steatotic Liver Disease Patients.

BACKGROUND/AIM: Metabolic dysfunction-associated steatotic liver disease (MASLD) is often silent and...

Noninvasive detection and differentiation of gastric malignancy using cell-free DNA biomarkers.

INTRODUCTION: Gastric cancer remains a major global health burden, with high mortality driven by lat...

Bibliometric visualization analysis of the application of artificial intelligence in gastrointestinal surgery recent 10 years.

To systematically analyze the current status and future trends of artificial intelligence (AI) in ga...

Machine learning-based binary classification of elevated HbA1c (≥6.5 %) for risk assessment.

OBJECTIVE: One of the most important biomarkers for evaluating long-term glycemic management and est...

Artificial intelligence-driven 3-dimensional simulation system for enhanced preoperative planning in gastric cancer surgery: a retrospective validation study.

BACKGROUND: Few studies have developed artificial intelligence (AI) systems for the automatic recogn...

Predictors of glycemic control with imeglimin for type 2 diabetes: Results of machine learning analyses using clinical trial data.

INTRODUCTION: Identifying patient characteristics predictive of treatment response is crucial for op...

AI-powered intestinal ultrasound in inflammatory bowel disease: Advancing toward automated disease assessment.

The management of inflammatory bowel disease (IBD) relies on accurate disease assessment and close m...

Correction: Curriculum for safe and effective use of artificial intelligence in endoscopy: European Society of Gastrointestinal Endoscopy (ESGE) Position Statement.

Meta-analysis of faecal microbiome studies followed by machine learning to identify intestinal disease-specific taxonomic signatures.

Alterations in the gut microbiome have been found to be associated with both inflammatory bowel dise...

Non-invasive diagnosis of metabolic dysfunction-associated steatotic liver disease: Current status, challenges, and future directions.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most prevalent liver disease...

Cross-modality fusion of hematology-based digital and molecular biomarkers for intelligent epidemiological screening and surveillance of hepatocellular carcinoma.

Early detection of hepatocellular carcinoma (HCC) remains a critical challenge due to the disease's ...

Curriculum for safe and effective use of artificial intelligence in endoscopy: European Society of Gastrointestinal Endoscopy (ESGE) Position Statement.

The European Society of Gastrointestinal Endoscopy (ESGE) has identified a critical need to establis...