Deep learning-based system for detecting gastric neoplasms during upper gastrointestinal endoscopy

White light endoscopy is a pivotal first-line tool for the detection of gastric neoplasms. However, these neoplasms can be missed due to the subtle nature of these lesions and varying skill among endoscopists. A study at Renmin Hospital of Wuhan University (China) evaluated an artificial intelligence system designed to detect focal lesions and diagnose gastric neoplasms. The study found that the use of an AI system during gastrointestinal endoscopy significantly reduced the gastric neoplasm miss rate, from 27.3% to 6.1% (p=0.015).