Gastroenterology

Selection of the best artificial intelligence techniques for analysis of gastrointestinal endoscopic images.

BACKGROUND AND STUDY AIM: Comprehensive identification and prioritization of artificial intelligence...

An integrated in silico, in vitro, and machine learning pipeline for rapid discovery of antioxidant peptides and co-product lipids from goat liver.

Goat liver abundant in high-quality protein is a by-product during meat processing, which is current...

A CT-based radiomics model for classification of chronic pancreatitis: new biomarkers for diagnosis and severity staging.

OBJECTIVES: To develop and validate CT-based radiomics models for the identification of chronic panc...

Double Graph Attention Network for predicting non-alcoholic fatty liver disease in patients with type 2 diabetes.

Type 2 diabetes mellitus (T2DM) is a chronic metabolic disease, while non-alcoholic fatty liver dise...

Anti-Inflammatory Properties of Dendrobium: A Systematic Review of Pharmacological Mechanisms.

ETHNOPHARMACOLOGICAL RELEVANCE: In Traditional Chinese Medicine (TCM), Dendrobium species have long ...

Multicenter Prospective Cohort Study on Clinical Outcomes and Fibrosis Patterns in Biopsy-Proven Steatotic Liver Disease Subtypes.

BACKGROUND & AIMS: Clinical outcomes and histological characteristics of biopsy-proven steatotic liv...

Organ preservation in rectal cancer: an endoscopist's perspective on current evidence and future directions.

Rectal cancer management has increasingly shifted toward organ-preserving strategies that aim to mai...

An explainable AI workflow integrating automated volumetric body composition analysis for predicting pathological grading of gastroenteropancreatic neuroendocrine neoplasms: a multicenter cohort study.

BACKGROUND: Gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) are heterogeneous tumors with...

Differentiation of focal liver lesions in contrast-enhanced ultrasound using a heuristic-guided hybrid machine-learning framework.

PURPOSE: Sonazoid contrast-enhanced ultrasound (CEUS) offers valuable diagnostic information on hepa...

Forecasting Waitlist Trajectories for Patients With Metabolic Dysfunction-Associated Steatohepatitis Cirrhosis: A Neural Network Competing Risk Analysis.

BACKGROUND: Metabolic dysfunction-associated steatohepatitis (MASH) cirrhosis is a leading indicatio...

Machine learning based screening of potential paper mill publications in cancer research: methodological and cross sectional study.

OBJECTIVES: To train and validate a machine learning model to distinguish paper mill publications fr...

Non-invasive liquid biopsy based on metabolomic profiling improves diagnosis and early warning of severe acute pancreatitis.

To identify novel diagnostic biomarkers for acute pancreatitis (AP) and facilitate the early predict...

Interpretable machine learning model for predicting 5-Year postoperative recurrence risk in patients with stage III colon cancer using preoperative laboratory tests: a two-centre study.

BACKGROUND: Colorectal cancer (CRC) is one of the most prevalent malignant diseases worldwide and di...

Accelerated Reduced Field of View T2-Weighted Imaging of Pancreaticobiliary Disorders Using Deep Learning-Based Reconstruction: Reduction of Acquisition Time and Improvement of Image Quality.

BACKGROUND: Reduced field-of-view (rFOV) T2WI improves in-plane spatial resolution. Deep learning-ba...

18F-FDG PET radiomics model for predicting TARE response in patients with colorectal cancer liver metastases.

PURPOSE: Predicting treatment response in patients with colorectal cancer liver metastases (CRCLM) w...

Application of AI to Gastrointestinal and Liver Diseases - Real Results from Artificial Intelligence.

Two decades of artificial intelligence in colon cancer diagnosis and treatment: a bibliometric analysis of research trends (2003-2023).

Urine Proteomics Identifies Biomarkers for Diagnosis and Fibrosis Severity in Pediatric Chronic Pancreatitis.

INTRODUCTION: Reliable biomarkers for the diagnosis of chronic pancreatitis (CP) and pancreatic fibr...

A machine learning-based transcriptomic signature for predicting tumor recurrence after curative resection in T1 colorectal cancer: a retrospective multicenter cohort study (The Tw1CE trial).

BACKGROUND: T1 colorectal cancer (T1 CRC) is increasingly treated with curative-intent endoscopic re...

Artificial Intelligence Driven Virtual Screening and Molecular Docking Approaches Identified LIFR, BTG2, EPHX2, and PAK3 as Targets and BI-2536, AP-24534, and AZ-628 as Repurposed Drugs for PDAC.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive and lethal tumors worldwide, w...

Development of a machine learning-based model for prediction of diabetes risk in patients with metabolic dysfunction-associated steatotic liver disease (MASLD).

BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a leading chronic li...