Gastroenterology

Metabolic factor-based machine learning model for mortality prediction in acute hepatitis E: Development and validation from a dual-center cohort.

BACKGROUND: Hepatitis E virus (HEV) infection remains a major cause of liver failure with high short...

Multiparametric MRI-Based Deep Learning and Radiomics for Predicting Progression-Free Survival Benefit in Patients with Hepatocellular Carcinoma Treated with Immunotherapy and Targeted Therapy Plus Transarterial Chemoembolization: A Bicentric Study.

RATIONALE AND OBJECTIVES: The non-invasive biomarkers for predicting progression-free survival (PFS)...

[Dual role of tea consumption in gastrointestinal disease risks: analysis using a risk prediction model integrating interpretable machine learning and large language model].

OBJECTIVES: To explore the correlation of tea consumption with risks of gastrointestinal diseases us...

Identifying a better-prognosis pancreatic cancer from its benign inflammatory mimic: a machine learning approach with contrast-enhanced ultrasound for early intervention.

PURPOSE: Hypervascular pancreatic ductal adenocarcinoma (PDAC) and mass-forming pancreatitis (MFP) r...

Predicting treatment response to neoadjuvant chemotherapy in locally advanced rectal cancer: A combined deep learning and machine learning approach utilizing longitudinal multi-sequence MRI.

PURPOSE: To develop and validate deep leaning-based machine learning models using longitudinal multi...

Non-invasive prediction of Ki-67 expression in gastric cancer using AI-based dual-energy CT: a multicenter study.

OBJECTIVE: To develop and validate a machine learning model based on quantitative parameters of dual...

Exploring an Intermediate Colorectal Cancer Screening Test Based on Stool Proteomics and Machine Learning for Optimizing the Selection of Patients for Colonoscopy Identified from FIT.

The fecal immunochemical test (FIT) for detecting fecal occult blood, used alone or in combination w...

Neoadjuvant Radiation is Causally Linked to Increased Operative Time and Perioperative Blood Transfusion in Pancreatic Ductal Adenocarcinoma.

INTRODUCTION: Blood transfusion in patients undergoing surgical resection for pancreatic ductal aden...

Evaluating the role of the main pancreatic duct in intraductal papillary mucinous neoplasm grading: A multi-structure radiomics-based machine learning approach.

PURPOSE: The purpose of this study was to evaluate the contribution of radiomics features extracted ...

Deep Learning Integration of Endoscopic Ultrasound Features and Serum Data Reveals LTB4 as a Diagnostic and Therapeutic Target in ESCC.

BACKGROUND: Early diagnosis and accurate prediction of treatment response in esophageal squamous cel...

AI portal tract detection and characterisation for a regional analysis of steatosis and inflammation in MASLD, MASH and AIH.

AIMS: Annotation of liver biopsies for disease staging is increasingly aided by digital pathology; h...

Intelligent identification and targeted intervention of GRP75-caused drug resistant hepatocellular carcinoma, a study based on radiomics, machine learning, and molecular pharmacology.

BACKGROUND: Tumor heterogeneity mediated drug resistance was a core clinical challenge to improve th...

Comment on "Machine learning model for predicting a high comprehensive complication index following rectal cancer surgery".

FOXK1 induced upregulation of KIF20A promotes hepatocellular carcinoma progression via Wnt/β-Catenin/EMT signaling.

Liver cancer ranks sixth in incidence and third in mortality worldwide, with hepatocellular carcinom...

The consensus molecular subtypes of esophageal squamous cell carcinoma.

Esophageal squamous cell carcinoma (ESCC) lacks a standardized classification system, resulting in i...

Oncogenic function and transcriptional dynamics of MYCN in liver tumorigenesis.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality. It is often diagnosed...

[AI and clinical reasoning : between promises and the risks of "deskilling"].

The rise of AI in healthcare offers major potential for diagnosis and learning but also exposes to a...

Universal gene-level bimodality in natural microbial communities.

Bimodality-the coexistence of two peaks in trait distributions-is common in natural ecosystems. In m...

Letter Regarding "Artificial Intelligence Model for Automated Identification of Bowel Preparation for Colonoscopy (AI-PREPOO): A Multicenter Study".

Hepatic and abdominal adiposity in type 2 diabetes as assessed with machine learning on computed tomography scans.

AIMS: The combined assessment of multiple abdominal imaging traits in relation to type 2 diabetes re...

Artificial intelligence enhances screening efficiency for inflammatory bowel disease clinical trials: a prospective study.

An LLM-based AI tool significantly improved identification of potentially eligible patients and scre...