Gastroenterology

Integrating multi-omics data for enhanced prognosis prediction in gastric cancer post-neoadjuvant therapy.

BACKGROUND: Neoadjuvant therapy is crucial for locally advanced gastric cancer (LAGC), yet response ...

Machine Learning Analysis of Serum Metabolomics for Multi-Disease Classification and Proteome-Metabolome Pathway Insights in T2D, IBD, and CRC.

Type 2 diabetes (T2D), inflammatory bowel disease (IBD), and colorectal cancer (CRC) share overlappi...

IL11⁺ fibroblasts are implicated in non-response to anti-TNFα via fibrosis in inflammatory bowel disease.

Inflammatory bowel disease (IBD) is frequently accompanied by intestinal fibrosis, with non-response...

Calculation and evaluation of the effective withdrawal time of colonoscopy on the basis of internimage.

Urinary extracellular vesicle miRNA signature reflects pancreatic islet stress in type 2 diabetes.

INTRODUCTION: Type 2 diabetes (T2D) is a progressive metabolic disorder characterized by insulin res...

Flexible IMU Sensor Array For 3D Colonoscope Shape Reconstruction and AI-Based Loop Detection.

Looping during colonoscopy procedures is a major cause of patient discomfort and increases the risk ...

A multimodal approach integrating NK cell-associated gene signatures and pathomics to predict colon adenocarcinoma prognosis.

Gut microbiome and metabolic health: mechanisms and precision interventions.

The gut microbiome is increasingly recognized as a fundamental regulator of metabolic health, shapin...

Harnessing machine learning to non-invasively evaluate mucosal healing in children with Crohn's disease.

A novel autoantibody panel as potential diagnostic markers for hepatocellular carcinoma.

AIMS: Hepatocellular carcinoma (HCC) represents a major global health burden. Tumor-associated autoa...

Mucinous vs. non-mucinous pancreatic cysts: diagnostic keys on CT and MRI.

The prevalence of incidentally detected pancreatic cystic lesions has increased substantially with t...

Beta cell microRNAs function as molecular hubs of type 1 diabetes pathogenesis and as biomarkers of diabetes risk.

AIMS/HYPOTHESIS: Clinically actionable biomarkers that accurately reflect the health status of the b...

Interpretable machine learning models based on CMR radiomics for predicting left ventricular diastolic dysfunction in patients with metabolic-associated steatotic liver disease and type 2 diabetes mellitus.

BACKGROUND: Obesity-induced left ventricular diastolic dysfunction (LVDD), associated with ectopic f...

Understanding Perceived Forehead Changes Post-Endoscopic Brow Lift: The Impact of Frontalis Muscle Contraction.

BACKGROUND: Endoscopic brow lift surgery is increasingly performed, yet there are concerns about pot...

APSevLM: Acute Pancreatitis Severity Language Model.

Approximately one-fifth of patients with acute pancreatitis (AP) develop severe forms, which are ass...

[Prevention in Gastroenterology].

Gastroenterology offers a broad, evidence-based range of preventive measures that goes beyond colore...

Development and validation of an ensemble machine learning model to predict survival in locally advanced rectal cancer: A multicenter, retrospective study.

BACKGROUND: Patients identified with locally advanced rectal cancer (LARC) demonstrate a varied prog...

Design of a soft robotic endoscope with enhanced bending and AI-based prediction.

Minimally invasive surgery (MIS) increasingly benefits from soft robotic platforms that offer enhanc...

High-precision classification of WCE-based gastrointestinal abnormality using a fusion deep learning approach.

Gastrointestinal abnormalities are widespread worldwide and pose a significant health challenge. How...

Distinct signatures in the human gut and oral microbiomes of gastric cancer.

Microbiome dysbiosis is increasingly recognized as a hallmark of gastric cancer (GC). Here, we analy...

Machine learning models for predicting microvascular invasion in hepatocellular carcinoma with three-dimensional whole-lesion 18F-FDG PET radiomics.

OBJECTIVE: To estimate the performance of machine learning models based on preoperative three-dimens...