Gastroenterology

Usefulness of Artificial Intelligence for Surgical Support in Robot-assisted Distal Pancreatectomy: A Preliminary Case Report.

BACKGROUND/AIM: The incidence of postoperative complications in minimally-invasive surgery for pancr...

Comparative Performance of Artificial Intelligence-Based Computer-Aided Detection Systems for Colorectal Polyps: A Systematic Review and Network Meta-Analysis.

BACKGROUND AND AIMS: Computer-aided detection (CADe) is anticipated to enhance adenoma detection rat...

Deep Learning for Automated Tumor Segmentation of Rectal Cancer on T2-Weighted Magnetic Resonance Images.

PURPOSE: To develop a deep learning (DL)-based automated segmentation model for rectal cancer on T2-...

A metabolite-augmented FIB-4 machine learning panel achieves superior liver fibrosis staging in chronic liver disease.

Accurate, non-invasive liver fibrosis detection is essential for chronic liver disease management, p...

X-LAT-Net: An Interpretable Lightweight Axial Transformer Network for Pancreatic CT Segmentation.

Accurate segmentation of the pancreas in CT images is notoriously difficult due to its deep-seated a...

Perspectives from machine learning and multi-omics to decoding the effects of VDAC2 malignant subsets on tumor evolution.

VDAC2's known role in cancer and immune regulation via enhancing the CD8+ T cell-mediated killing, a...

The Gut-Liver Axis in Metabolic Dysfunction-Associated Steatotic Liver Disease: From Mechanistic Insights to Precision Therapeutics.

Metabolic dysfunction-associated steatotic liver disease (MASLD) has become the most prevalent chron...

[Machine learning and radiomics-based model for predicting response to lenvatinib combined with TACE in patients with unresectable hepatocellular carcinoma].

Objective: To evaluate the predictive value of machine learning combined with radiomics for treatmen...

Artificial Intelligence prognostication of liver disease using imaging.

Accurate prognostic tools in patients with chronic liver disease (CLD) have the potential to improve...

Whole Metagenomic Profiling Identifies a Gut Microbial Signature for Chronic Pancreatitis via Machine Learning.

BACKGROUND: Pancreatitis significantly alters the microbial composition of the oral and intestinal c...

Keypoint detection network for needle localization on intra-procedural MRI in MRI-guided liver interventions.

PURPOSE: Segmentation neural networks have demonstrated promising results for interventional needle ...

Integration of protein and metabolomic blood biomarkers enhances classification of radiation exposure in X-irradiated humanized mice.

PURPOSE: The general population is at risk of exposure to ionizing radiation due to nuclear warfare,...

Machine learning prediction of common bile duct stones using synthetic data to guide emergency ERCP decisions.

Endoscopic retrograde cholangiopancreatography (ERCP) remains the standard for common bile duct (CBD...

Deep learning-based detection of bowel sound events in continuous recordings.

Machine learning identifies a 10-gene signature predicting hepatocellular carcinoma recurrence and immune-metabolic reprogramming.

BACKGROUND: Hepatocellular carcinoma (HCC) remains a major cause of cancer-related mortality, with f...

Dual-Peptide Nanoplatform: Mesoporous Silica Nanoparticles Functionalized With a Cell-Penetrating Peptide and Loaded With Rationally Designed Antimicrobial Peptides for Tuberculosis Therapy.

Tuberculosis remains a major infectious disease worldwide and demands new therapeutic approaches cap...

Univariate- and machine learning-based plasma metabolite signature differentiates PSC-IBD from IBD and is predicted to be driven by gut microbial changes.

INTRODUCTION: Inflammatory bowel disease (IBD) is a group of chronic inflammatory conditions of the ...

Domain specific multimodal large language model for automated endoscopy reporting with multicenter prospective validation.

Accurate endoscopy reports are crucial for the diagnosis and management of patients with upper gastr...

Network toxicology and machine learning revealed the association between non-alcoholic fatty liver disease induced by polystyrene nanoplastics.

This study systematically evaluated the hepatotoxic potential of common microplastic monomers using ...

Cell Painting for cytotoxicity and mode-of-action analysis in primary human hepatocytes.

Scalable, human-relevant approaches for detecting compound modes of action are needed to improve che...

Hypergraph Representations of Single-Cell RNA Sequencing Data for Improved Cell Clustering.

MOTIVATION: Single-cell RNA sequencing (scRNA-seq) data analysis is often performed using network pr...