Gastroenterology

Habitat Radiomics Based on MRI for Predicting Metachronous Liver Metastasis in Locally Advanced Rectal Cancer: a Two‑center Study.

RATIONALE AND OBJECTIVES: This study aimed to explore the feasibility of using habitat radiomics bas...

Application of artificial intelligence in the diagnosis of malignant digestive tract tumors: focusing on opportunities and challenges in endoscopy and pathology.

BACKGROUND: Malignant digestive tract tumors are highly prevalent and fatal tumor types globally, of...

Preoperative assessment in lymph node metastasis of pancreatic ductal adenocarcinoma: a transformer model based on dual-energy CT.

BACKGROUND: Deep learning(DL) models can improve significantly discrimination of lymph node metastas...

An artificial intelligence model utilizing endoscopic ultrasonography for differentiating small and micro gastric stromal tumors from gastric leiomyomas.

BACKGROUND: Gastric stromal tumors (GSTs) and gastric leiomyomas (GLs) represent the primary subtype...

Comprehensive analysis of scRNA-seq and bulk RNA-seq data via machine learning and bioinformatics reveals the role of lysine metabolism-related genes in gastric carcinogenesis.

BACKGROUND: Gastric cancer (GC) is a highly aggressive and heterogeneous cancer with extremely compl...

Novel deep learning algorithm based MRI radiomics for predicting lymph node metastases in rectal cancer.

To explore the value of applying the MRI-based radiomic nomogram for predicting lymph node metastasi...

Letter to the editor: "Prognosis of major bleeding based on residual variables and machine learning for critical patients with upper gastrointestinal bleeding: A multicenter study".

T-cell receptor dynamics in digestive system cancers: a multi-layer machine learning approach for tumor diagnosis and staging.

BACKGROUND: T-cell receptor (TCR) repertoires provide insights into tumor immunology, yet their vari...

Pseudotargeted metabolomics profiles potential damage-associated molecular patterns as machine learning predictors for acute pancreatitis.

Acute pancreatitis (AP) is a common gastrointestinal disease characterized by pancreatic cell damage...

Enhancing polyp classification: A comparative analysis of spatio-temporal techniques.

Colorectal cancer (CRC) is a major health concern, ranking as the third deadliest cancer globally. E...

Identification of patients at risk for pancreatic cancer in a 3-year timeframe based on machine learning algorithms.

Early detection of pancreatic cancer (PC) remains challenging largely due to the low population inci...

Gap-App: A sex-distinct AI-based predictor for pancreatic ductal adenocarcinoma survival as a web application open to patients and physicians.

In this study, using RNA-Seq gene expression data and advanced machine learning techniques, we ident...

Next questions on gastrointestinal stromal tumors: unresolved challenges and future directions.

PURPOSE OF REVIEW: Despite remarkable progress in the management of gastrointestinal stromal tumors ...

Randomized Trial on Electroacupuncture for Recovery of Postoperative Gastrointestinal Function Based on Long-Term Monitoring Device.

BACKGROUND: This research aimed to explore the efficacy and safety of electroacupuncture in promotin...

Explainable machine learning for the assessment of donor grafts in liver transplantation.

BACKGROUND AND AIM: The shortage of liver grafts compared to recipients necessitates precise organ a...

101 Machine Learning Algorithms for Mining Esophageal Squamous Cell Carcinoma Neoantigen Prognostic Models in Single-Cell Data.

Esophageal squamous cell carcinoma (ESCC) is one of the most aggressive malignant tumors in the dige...

Deep learning-based uncertainty quantification for quality assurance in hepatobiliary imaging-based techniques.

Recent advances in deep learning models have transformed medical imaging analysis, particularly in r...

LKAN: LLM-Based Knowledge-Aware Attention Network for Clinical Staging of Liver Cancer.

Clinical staging of liver cancer (CSoLC), an important indicator for evaluating primary liver cancer...

C2BNet: A Deep Learning Architecture With Coupled Composite Backbone for Parasitic Egg Detection in Microscopic Images.

Internet of Medical Things (IoMT) enabled by artificial intelligence (AI) technologies can facilitat...

Identification of Crohn's Disease-Related Biomarkers and Pan-Cancer Analysis Based on Machine Learning.

: In recent years, the incidence of Crohn's disease (CD) has shown a significant global increase, wi...

Early detection of esophageal cancer: Evaluating AI algorithms with multi-institutional narrowband and white-light imaging data.

Esophageal cancer is one of the most common cancers worldwide, especially esophageal squamous cell c...