AI Medical Compendium Journal:
Gastrointestinal endoscopy

Showing 41 to 50 of 104 articles

Simplified robot-assisted endoscopic submucosal dissection for esophageal and gastric lesions: a randomized controlled porcine study (with videos).

Gastrointestinal endoscopy
BACKGROUND AND AIMS: Effective countertraction is a main challenging issue in endoscopic submucosal dissection (ESD). Several countertraction methods have been developed to address this issue. The aim of this study was to compare the efficacy of ESD ...

Real-time automated diagnosis of colorectal cancer invasion depth using a deep learning model with multimodal data (with video).

Gastrointestinal endoscopy
BACKGROUND AND AIMS: The optical diagnosis of colorectal cancer (CRC) invasion depth with white light (WL) and image-enhanced endoscopy (IEE) remains challenging. We aimed to construct and validate a 2-modal deep learning-based system, incorporated w...

Artificial intelligence for the assessment of bowel preparation.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: A reliable assessment of bowel preparation is important to ensure high-quality colonoscopy. Current bowel preparation scoring systems are limited by interobserver variability. This study aimed to demonstrate objective assessment ...

Real-time artificial intelligence for detecting focal lesions and diagnosing neoplasms of the stomach by white-light endoscopy (with videos).

Gastrointestinal endoscopy
BACKGROUND AND AIMS: White-light endoscopy (WLE) is the most pivotal tool to detect gastric cancer in an early stage. However, the skill among endoscopists varies greatly. Here, we aim to develop a deep learning-based system named ENDOANGEL-LD (lesio...

Artificial intelligence for automatic diagnosis of biliary stricture malignancy status in single-operator cholangioscopy: a pilot study.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: The diagnosis and characterization of biliary strictures (BSs) is challenging. The introduction of digital single-operator cholangioscopy (DSOC) that allows direct visual inspection of the lesion and targeted biopsy sampling sign...

Deep learning model for diagnosing gastric mucosal lesions using endoscopic images: development, validation, and method comparison.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: Endoscopic differential diagnoses of gastric mucosal lesions (benign gastric ulcer, early gastric cancer [EGC], and advanced gastric cancer) remain challenging. We aimed to develop and validate convolutional neural network-based ...

Deep learning system compared with expert endoscopists in predicting early gastric cancer and its invasion depth and differentiation status (with videos).

Gastrointestinal endoscopy
BACKGROUND AND AIMS: We aimed to develop and validate a deep learning-based system that covers various aspects of early gastric cancer (EGC) diagnosis, including detecting gastric neoplasm, identifying EGC, and predicting EGC invasion depth and diffe...