Copyright
©The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Jun 7, 2021; 27(21): 2818-2833
Published online Jun 7, 2021. doi: 10.3748/wjg.v27.i21.2818
Published online Jun 7, 2021. doi: 10.3748/wjg.v27.i21.2818
Requirements for implementation of artificial intelligence in the practice of gastrointestinal pathology
Hiroshi Yoshida, Department of Diagnostic Pathology, National Cancer Center Hospital, Tokyo 104-0045, Japan
Tomoharu Kiyuna, Digital Healthcare Business Development Office, NEC Corporation, Tokyo 108-8556, Japan
Author contributions: Yoshida H and Kiyuna T contributed equally to this work.
Conflict-of-interest statement: All authors have no competing interests to be declared.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Hiroshi Yoshida, MD, PhD, Staff Physician, Department of Diagnostic Pathology, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, Japan. hiroyosh@ncc.go.jp
Received: February 4, 2021
Peer-review started: February 4, 2021
First decision: March 6, 2021
Revised: March 16, 2021
Accepted: April 28, 2021
Article in press: April 28, 2021
Published online: June 7, 2021
Processing time: 111 Days and 22.5 Hours
Peer-review started: February 4, 2021
First decision: March 6, 2021
Revised: March 16, 2021
Accepted: April 28, 2021
Article in press: April 28, 2021
Published online: June 7, 2021
Processing time: 111 Days and 22.5 Hours
Core Tip
Core Tip: The advances in artificial intelligence (AI) will revolutionize medical practice, as well as other areas of medicine. Deep learning algorithms have shown promising benefits in various areas of diagnostic histopathology. Despite this, AI technology is not widely used as a medical device and is not approved by a regulatory authority. Thus, implying that certain improvements in the development process are still necessary for the implementation of AI in the real-life histopathology-practice. This paper aims to provide a review of recent AI developments in gastrointestinal pathology and the challenges in their implementation.