Gastroenterology

Screening of Demethylation-related Biomarkers and Exploration of Regulatory Mechanisms in Esophageal Cancer Patients Based on Machine Learning and Mendelian Randomization.

INTRODUCTION: The aggressive cancer known as Esophageal Squamous Cell Carcinoma (ESCC) has a dismal prognosis. Epigenetic changes such as demethylation have a significant impact on ESCC development and progression. METHODS: WGCNA and differential expression analysis of GEO datasets identified tumorrelated demethylation genes. Random Survival Forest (RSF), univariate Cox regression, and LASSO-Cox m...

Pancreatic Cancer Risk Stratification Across Diabetes Stages: Development and Internal Validation of a Machine Learning Model.

BACKGROUND: Pancreatic cancer is diagnosed at advanced stages in diabetes patients. Existing prediction models require complete historical data and focus on new-onset diabetes, limiting applicability. We developed a machine learning model to handle missing data and perform across the diabetes spectrum. METHODS: Retrospective cohort study using TriNetX electronic health records. Patients with hemog...

Molecular Encoding during Amplification Enables Multiplex Nanopore Profiling of Small Noncoding RNAs.

Many cancers are characterized by the coordinated dysregulation of multiple small noncoding RNAs (sncRNAs), yet fluorescence-based assays such as quan...

Noninvasive prediction of severe histopathology in drug-induced liver injury using a dual elastography-based machine learning model.

OBJECTIVES: To develop and validate a machine learning (ML) model integrating dual elastography, clinical features, and serum biomarkers for noninvasi...

Exploring the gut-lung axis in post-liver transplant acute lung injury: A multi-omics approach.

Acute lung injury (ALI) is a significant post-operative complication of liver transplant (LT), with mounting evidence suggesting a role for the gut-lu...

Deep Learning Predicts Mutations and Outcomes in Gastrointestinal Stromal Tumors from Whole-Slide Images.

Gastrointestinal stromal tumor (GIST) is the most common gastrointestinal mesenchymal tumor, driven by tyrosine-protein kinase (KIT) and platelet-deri...

The atlas of abdominal organ remodeling in hepatocellular carcinoma patients: An artificial intelligence-based multicenter imaging study.

BACKGROUND: Morphological changes of abdominal organs in hepatocellular carcinoma (HCC) remain uncharacterized. This study aimed to automatically quan...

Radiological Assessment of Liver and Biliary Neoplasms.

Primary liver cancer, encompassing hepatocellular carcinoma and cholangiocarcinoma, represents a growing global health burden with significant morbidi...

Integrative machine learning and multi-omics analysis reveals ATIC as a promoter of hepatocellular carcinoma progression.

Autophagy plays a non-negligible role in the progression and immune regulation of hepatocellular carcinoma (HCC). An integrated analysis of the autoph...

Machine learning models for non-invasive endometriosis triage using a laparoscopically and histologically verified cohort.

OBJECTIVE: To develop and internally validate machine-learning models for non-invasive triage of women at risk for endometriosis using structured clin...

Deep learning layer-specific collagen quantification correlates with activity and is associated with outcomes in Crohn's disease.

BACKGROUND & AIMS: Intestinal fibrosis remains a major unmet need in inflammatory bowel disease (IBD). Although collagen deposition is the defining fe...

Metabolomic machine learning predictor for the diagnosis of alcohol-associated liver disease.

BACKGROUND: It is urgent to find novel non-invasive biomarkers that can accurately diagnose alcohol-associated liver disease (ALD). The objective of t...

Deep learning-driven inversion framework for shear modulus estimation in magnetic resonance elastography.

PURPOSE: The multimodal direct inversion (MMDI) algorithm is widely used in magnetic resonance elastography (MRE) to estimate tissue shear stiffness b...

Comment on "Development and validation of machine learning models for mortality risk stratification in acute pancreatitis patients complicated by acute kidney injury".

A histopathologically verified dataset of magnifying narrow-band imaging endoscopy for classifying the gastric precancerous cascade.

Gastric cancer is a leading cause of mortality worldwide, yet the development of computer-aided diagnosis (CAD) systems for its early detection is hin...

High-throughput identification of bacterial β-glucuronidase inhibitors using machine learning.

The human gut microbiome plays a vital role in regulating host physiological functions and influencing the pharmacokinetics of interventions, particul...

Mechanism of liquiritin from Codonopsis pilosula-Glycyrrhiza uralensis extract in alleviating piglet weaning stress via binding to alpha-1-microglobulin/bikunin precursor by machine learning and molecular dynamics simulation.

Weaning stress is a prevalent pathological condition in pig farming, primarily triggered by factors such as nutritional imbalance, oxidative stress, i...

Impact of Availability of Computer-Aided Detection Devices on Adenoma Detection During Colonoscopy: A Cluster Randomized Study.

BACKGROUND AND AIMS: Endoscopists' colonoscopy adenoma detection rates (ADR) are inversely associated with their patients' risk of post-colonoscopy co...

A Holistic Eating Monitoring System Enabled by Textile Strain Sensors and Hierarchical Network.

Wearable sensors have prompted human dynamic monitoring by quantifying physiological and biomechanical signals in daily life. However, existing approa...

AI in esophageal cancer: advances, barriers to clinical translation, and perspectives for digital health.

BACKGROUND: Esophageal cancer (EC) remains one of the leading causes of cancer-related mortality worldwide. Accurate staging, treatment planning, and ...