Published online Jun 28, 2021. doi: 10.3748/wjg.v27.i24.3543
Peer-review started: January 25, 2021
First decision: March 29, 2021
Revised: April 9, 2021
Accepted: May 21, 2021
Article in press: May 21, 2021
Published online: June 28, 2021
Recently, studies in many medical fields have reported that image analysis based on artificial intelligence (AI) can be used to analyze structures or features that are difficult to identify with human eyes. To diagnose early gastric cancer, related efforts such as narrow-band imaging technology are on-going. However, diagnosis is often difficult. Therefore, a diagnostic method based on AI for endoscopic imaging was developed and its effectiveness was confirmed in many studies. The gastric cancer diagnostic program based on AI showed relatively high diagnostic accuracy and could differentially diagnose non-neoplastic lesions including benign gastric ulcers and dysplasia. An AI system has also been developed that helps to predict the invasion depth of gastric cancer through endoscopic images and observe the stomach during endoscopy without blind spots. Therefore, if AI is used in the field of endoscopy, it is expected to aid in the diagnosis of gastric neoplasms and determine the application of endoscopic therapy by predicting the invasion depth.
Core Tip: Recently, image analysis based on artificial intelligence (AI) has been applied in the field of diagnostic endoscopy in gastroenterology, and active research is also being conducted on gastric neoplasms. Several studies reported that AI-based early gastric cancer diagnosis and the prediction of invasion depth showed excellent performance and that the differential diagnosis from non-neoplastic lesions including benign gastric ulcers was possible. Therefore, if AI is used in clinical practice, it can be expected to help diagnose gastric neoplasms and determine treatment methods.