Gastroenterology

Automated quantification of T1 and T2 relaxation times in liver mpMRI using deep learning: a sequence-adaptive approach.

OBJECTIVES: To evaluate a deep learning sequence-adaptive liver multiparametric MRI (mpMRI) assessme...

Multi-class transformer-based segmentation of pancreatic ductal adenocarcinoma and surrounding structures in CT imaging: a multi-center evaluation.

OBJECTIVE: Accurate segmentation of pancreatic ductal adenocarcinoma (PDAC) and surrounding anatomic...

Endoscopic virtual ruler based on artificial intelligence technology.

Development of a circadian-related prognostic signature highlights RBM17 as a stemness regulator in liver cancer.

The liver exhibits extensive circadian regulation among organs. Epidemiological studies have substan...

Mucosal immune responses and intestinal microbiome associations in wild spotted hyenas (Crocuta crocuta).

Little is known about host-gut microbiome interactions within natural populations at the intestinal ...

Type 2 Diabetes Mellitus Remission, Dream or Reality? A Narrative Review of Current Evidence and Integrated Care Strategies.

Type 2 diabetes mellitus (T2DM) is a global health priority, with an estimated 629 million people pr...

Correction: Trends in the applications of artificial intelligence in fatty liver diseases.

Fecal gut microbiota and amino acids as noninvasive diagnostic biomarkers of Pediatric inflammatory bowel disease.

BACKGROUND AND AIMS: Fecal calprotectin (FCP) has limited specificity as diagnostic biomarker of ped...

Multi-omics integration of TPX2 in prognostic prediction in resectable hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a malignant tumor with high incidence and mortality rates globally...

Computer-aided detection for esophageal achalasia (with video).

OBJECTIVES: Achalasia is an esophageal motility disorder that impairs quality of life and is often m...

Letter to the editor: a commentary on "integrating machine learning and molecular docking to decipher the molecular network of aflatoxin b1-induced hepatocellular carcinoma.

Pretreatment Multi-sequence Contrast-Enhanced MRI to Predict Response to Immunotherapy in Unresectable Hepatocellular Carcinoma Using Transformer: A Multicenter Study.

Targeted combined immunotherapy (TCI) has shown certain antitumor effects in patients with unresect...

Integrative machine learning reveals the biological function and prognostic significance of α-ketoglutarate in gastric cancer.

Gastric cancer (GC) has a poor response to treatment, an unfavorable prognosis and a lack of reliabl...

Machine learning-based radiomics models for the prediction of metachronous liver metastases in patients with colorectal cancer: A multimodal study.

The aim of the present study was to investigate whether a multimodal radiomics model powered by mach...

Time-Gated Raman Spectroscopy Combined with Deep Learning for Rapid, Label-Free Histopathological Discrimination of Gastric Cancer.

Gastric cancer is one of the most common malignant tumors of the digestive system, with a high morta...

28-day all-cause mortality in patients with alcoholic cirrhosis: a machine learning prediction model based on the MIMIC-IV.

To develop and validate a machine learning prediction model for 28-day all-cause mortality in patien...

Deep learning neural network prediction of postoperative complications in patients undergoing laparoscopic right hemicolectomy with or without CME and CVL for colon cancer: insights from SICE (Società Italiana di Chirurgia Endoscopica) CoDIG data.

BACKGROUND: Postoperative complications in colorectal surgery can significantly impact patient outco...

Advancing artificial intelligence applicability in endoscopy through source-agnostic camera signal extraction from endoscopic images.

INTRODUCTION: Successful application of artificial intelligence (AI) in endoscopy requires effective...

Machine learning driven biomarker selection for medical diagnosis.

Recent advances in experimental methods have enabled researchers to collect data on thousands of ana...

Evaluating large language models for information extraction from gastroscopy and colonoscopy reports through multi-strategy prompting.

OBJECTIVE: To systematically evaluate large language models (LLMs) for automated information extract...

Evaluation of AI-Based Chatbots in Liver Cancer Information Dissemination: A Comparative Analysis of GPT, DeepSeek, Copilot, and Gemini.

BACKGROUND/OBJECTIVES: This study aimed to evaluate AI-based chatbots (GPT, DeepSeek, Copilot, Gemin...