摘要
Wireless capsule endoscopy(WCE)enables physicians to examine the gastrointestinal tract by transmitting images wirelessly from a disposable capsule to a data recorder.Although WCE is the least invasive endoscopy technique for diagnosing gastrointestinal disorders,interpreting a WCE study requires significant time effort and training.Analysis of images by artificial intelligence,through advances such as machine or deep learning,has been increasingly applied to medical imaging.There has been substantial interest in using deep learning to detect various gastrointestinal disorders based on WCE images.This article discusses basic knowledge of deep learning,applications of deep learning in WCE,and the implementation of deep learning model in a clinical setting.We anticipate continued research investigating the use of deep learning in interpreting WCE studies to generate predictive algorithms and aid in the diagnosis of gastrointestinal disorders.
