Gastroenterology

Effectiveness of AI-enhanced colonoscopy: A case-control study using real world evidence in a young screening age population.

BACKGROUND: Computer aided detection (CADe) colonoscopy has been shown in randomized controlled trials to improve detection of adenomatous colorectal polyps. However, in real-world settings the benefits are less clear. Our objective was to assess CADe colonoscopy compared to routine colonoscopy in a clinical practice setting in the Arab region with a low screening age (40 years old). METHODS: Afte...

Rapid, label-free cancer detection in fresh pancreatic tissue using deep learning and multispectral Mueller matrix polarimetry.

BACKGROUND: Frozen section (FS) tissue assessment is essential for guiding intraoperative surgical decision-making in oncology, particularly in procedures such as pancreatic ductal adenocarcinoma (PDAC) resections, where margin status critically impacts patient survival. The current gold standard, (FS), while widely used, suffers from notable limitations, including tissue artifacts, dependence on ...

Ranking-Aware Multiple Instance Learning for Histopathology Slide Classification: Development and Validation Study.

BACKGROUND: Multiple instance learning (MIL) is widely used for slide-level classification in digital pathology without requiring expert annotations. ...

Advances in multi-omics for esophageal squamous cell carcinoma: Diagnostic, prognostic, and therapeutic perspectives.

Esophageal squamous cell carcinoma (ESCC) remains a major health burden, particularly in Asia, with poor patient prognosis despite advancements in rad...

Machine learning-based prognostic model of stemness and angiogenesis-related genes for predicting prognosis and immune infiltration in patients with HCC.

Hepatocellular carcinoma (HCC), the predominant form of primary liver cancer, ranks as the fourth leading cause of cancer-associated mortality globall...

Comparison of artificial intelligence and multidisciplinary team recommendations in the management of colorectal cancer liver metastases.

Multidisciplinary teams (MDTs) are central to treatment planning for colorectal cancer liver metastases (CRCLM) but require time and consistent access...

Construction of a depression risk prediction model for hepatitis B patients based on machine learning strategy.

BACKGROUND: Hepatitis B (HBV) is a chronic viral infection that can lead to cirrhosis, liver failure, and liver cancer, and has a profound impact on t...

Discovery of High-Affinity Glutamine-Derived Peptides from Wheat Gliadin Targeting CaSR: a Computational Approach Integrating Deep Learning and Molecular Dynamics.

Calcium-sensing receptor (CaSR)-targeting agonist peptides play a crucial role in maintaining intestinal homeostasis. In this study, we integrated dee...

Expanded Indications in Advanced Endoscopic Resection of Malignant Gastrointestinal Lesions.

PURPOSE OF REVIEW: Endoscopic resection (ER) has transformed the management of early gastrointestinal (GI) malignancies by offering curative treatment...

Prediction of Fontan failure and correlates of Fontan-associated liver disease severity using machine learning and radiomic features from multi-parametric abdominal MRI.

BACKGROUND: Fontan-associated liver disease (FALD) is associated with morbidity and mortality in patients with palliated single ventricle congenital h...

Lipid nanoparticle-delivered ornithine transcarbamylase mRNA alleviates liver fibrosis in preclinical models.

BACKGROUND AND AIMS: Liver fibrosis poses a major health threat globally, with an acute shortage of effective treatments to stop or reverse its progre...

Corrigendum: Machine learning identifies activation of RUNX/AP-1 as drivers of mesenchymal and fibrotic regulatory programs in gastric cancer.

Integrating body composition analysis and machine learning for non-invasive identification of metabolic dysfunction-associated fatty liver disease: a large-scale health examination-based study.

Metabolic dysfunction-associated fatty liver disease (MAFLD) is a highly prevalent liver condition closely linked to obesity, insulin resistance, and ...

Integrated multi-dataset screening to predict prognosis and identify immunotherapy gene targets in hepatocellular carcinoma patients.

This study systematically predicts prognosis and key gene targets for immunotherapy in hepatocellular carcinoma (HCC) patients based on the joint scre...

Predicting health-related quality of life for patients with gastroesophageal cancer.

BACKGROUND: Gastroesophageal cancer has a poor prognosis, and treatment significantly impacts health-related quality of life (HRQoL). Accurate predict...

Automatic processing of gastrointestinal endoscopy referrals and patient instructions using large language models.

Artificial intelligence-assisted real-time nasopharyngeal cancer diagnostic model enhances rhinologist performance: a prospective multi-reader study.

BACKGROUND: Nasopharyngeal carcinoma (NPC) poses significant diagnostic challenges due to the anatomical complexity of the nasopharynx and reliance on...

Drug repositioning for human MKN45 gastric cancer mouse model using deep learning AI and experimental validation.

BACKGROUND: Gastric cancer (GC) requires novel therapies. This study employed artificial neural networks (ANNs) to repurpose existing drugs against GC...

IR Spectroscopy and Linear Support Vector Machine Analysis of Colorectal Liver Metastasis.

The Colorectal Liver Metastasis (CLM) library contains 756,096 full range Fourier transform infrared (FTIR) microscope imaging spectra of 14 frozen ti...

Comparison of balloon-occluded esophageal varices obliteration and endoscopic variceal ligation for high-risk esophageal varices of various diameters: a prospective randomized controlled trial.

BACKGROUND AND AIMS: Endoscopic variceal ligation (EVL) is associated with relatively high rebleeding rates in patients with large esophageal varices ...