Artificial intelligence for cancer detection of the upper gastrointestinal tract. Issue 2 (28th December 2020)

• Record Type: Journal Article
• Authors: Suzuki, Hideo; Yoshitaka, Tokai; Yoshio, Toshiyuki; Tada, Tomohiro
• Is Part Of: Digestive endoscopy. Volume 33:Issue 2(2021)
• Page Start: 254
• Page End: 262
• Publication Date: 2020-12-28
• Subjects: artificial intelligence -- esophageal squamous cell carcinoma -- gastric cancer -- helicobacter pylori -- pharyngeal cancer; Digestive organs -- Diseases -- Periodicals; Digestive organs -- Diseases -- Diagnosis -- Periodicals; Endoscopy -- Periodicals; Digestive System Diseases -- diagnosis -- Periodicals; Digestive System Diseases -- therapy -- Periodicals; Endoscopy -- Periodicals; 616.3
• DOI: 10.1111/den.13897
• Languages: English
• ISSNs: 0915-5635

Abstract

Abstract : In recent years, artificial intelligence (AI) has been found to be useful to physicians in the field of image recognition due to three elements: deep learning (that is, CNN, convolutional neural network), a high‐performance computer, and a large amount of digitized data. In the field of gastrointestinal endoscopy, Japanese endoscopists have produced the world's first achievements of CNN‐based AI system for detecting gastric and esophageal cancers. This study reviews papers on CNN‐based AI for gastrointestinal cancers, and discusses the future of this technology in clinical practice. Employing AI‐based endoscopes would enable early cancer detection. The better diagnostic abilities of AI technology may be beneficial in early gastrointestinal cancers in which endoscopists have variable diagnostic abilities and accuracy. AI coupled with the expertise of endoscopists would increase the accuracy of endoscopic diagnosis.