Copyright ©The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved.
Artif Intell Gastroenterol. Dec 28, 2021; 2(6): 141-156
Published online Dec 28, 2021. doi: 10.35712/aig.v2.i6.141
Artificial intelligence in pathological evaluation of gastrointestinal cancers
Anil Alpsoy, Aysen Yavuz, Gulsum Ozlem Elpek
Anil Alpsoy, Aysen Yavuz, Gulsum Ozlem Elpek, Department of Pathology, Akdeniz University Medical School, Antalya 07070, Turkey
Author contributions: Alpsoy A and Yavuz A performed the data acquisition; Elpek GO designed the outline and coordinated the writing of the paper; all authors equally contributed to the writing of the paper and preparation of the tables.
Conflict-of-interest statement: There is no conflict of interest to disclose.
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:
Corresponding author: Gulsum Ozlem Elpek, MD, Professor, Pathology, Akdeniz University Medical School, Dumlupınar bulvarı, Antalya 07070, Turkey.
Received: December 6, 2021
Peer-review started: December 6, 2021
First decision: December 13, 2021
Revised: December 19, 2021
Accepted: December 27, 2021
Article in press: December 27, 2021
Published online: December 28, 2021
Core Tip

Core Tip: Recently, based on improvements in efficient computational power and learning capacities, various artificial intelligence applications, such as image-based diagnosis and prognosis prediction, have emerged in many fields of pathology. This review comprehensively summarizes the current status of artificial intelligence applications in gastrointestinal cancers. The present data are promising for the use of artificial intelligence to diagnose tumors, evaluate prognostic parameters, and detect biomarker/genetic alterations. However, many challenges hinder the implication of artificial intelligence models in real pathological practice. Therefore, these challenges and suggested solutions are also briefly presented to improve the accuracy and relevance of artificial intelligence in pathological practice, including in gastrointestinal cancers.