Gastroenterology

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 disease (NAFLD) is the most prevalent chronic liver disease, which can progress to more severe liver diseases such as liver fibrosis, cirrhosis and hepatocellular carcinoma. Approximately 50%-70% of T2DM patients also have NAFLD. Traditional diagnostic methods like liver biopsy have limitations, making ...

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

ETHNOPHARMACOLOGICAL RELEVANCE: In Traditional Chinese Medicine (TCM), Dendrobium species have long been utilized to alleviate various inflammatory symptoms, particularly those characterized by Yin deficiency with internal heat and stomach deficiency-heat, including impaired fluid production, dysregulated stomach Qi, and poor appetite. The inflammatory response is regulated by multiple signaling p...

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 liver disease (SLD) subtypes remain understudied. We ...

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 maintain oncologic control while preserving bowel, ur...

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 rising incidence, necessitating precise preoperat...

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 hepatic lesions, but it is time-consuming. In this stu...

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 indication for liver transplantation (LT). Patients with MA...

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 from genuine cancer research articles, and to screen...

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 prediction of severe AP (SAP), this investigation charact...

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 displays significant heterogeneity. The aim of this ...

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-based reconstruction (DLR) has emerged as enhancing ...

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) who have undergone transarterial radioembolization ...

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 fibrosis severity are lacking, hindering effective tre...

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 resection, but tumor recurrence remains a critical f...

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, with limited effective treatments. Globally, the in...

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 liver disorder closely linked to diabetes mellitus (...

Advancing personalized prognostic assessment in rectal cancer through multi-instance deep learning.

PBPK Modeling Addresses Oral Absorption-Mediated Drug Interactions.

Absorption is the first and imperative step to understanding the pharmacokinetics (PK) and ADME (absorption, distribution, metabolism, and excretion) ...