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World J Clin Oncol. Sep 24, 2025; 16(9): 107993
Published online Sep 24, 2025. doi: 10.5306/wjco.v16.i9.107993
Role of artificial intelligence in screening and medical imaging of precancerous gastric diseases
Sergey M Kotelevets
Sergey M Kotelevets, Department of Propaedeutics of Internal Medicine, North Caucasus State Academy, Cherkessk 369000, Karachay-Cherkess Republic, Russia
Author contributions: Kotelevets SM contributed to this paper, designed the overall concept and outline of the manuscript, contributed to the design of the manuscript, contributed to the writing and editing the manuscript, illustrations, and review of literature.
Conflict-of-interest statement: The author reports no relevant conflicts of interest for this article.
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: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Sergey M Kotelevets, MD, Professor, Department of Propaedeutics of Internal Medicine, North Caucasus State Academy, Stavropolskaya Street 36, Cherkessk 369000, Karachay-Cherkess Republic, Russia. smkotelevets@mail.ru
Received: April 2, 2025
Revised: May 22, 2025
Accepted: August 25, 2025
Published online: September 24, 2025
Processing time: 174 Days and 11.8 Hours
Core Tip

Core Tip: Prevention of gastric cancer compose of consistent measures to identify precancerous gastric diseases and changes in the gastric mucosa. The first stage is population serological screening for atrophic gastritis. The next stages are endoscopic and morphological visualization of precancerous changes of varying severity. Evaluation of the results of population serological screening is not possible without machine data processing. Accuracy of visualization of endoscopic (macroscopic) and histological (microscopic) images is not possible without the use of convolutional neural networks and deep machine learning. The development and implementation of artificial intelligence will significantly increase the effectiveness of preventive measures.