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Copyright ©The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved.
Artif Intell Gastroenterol. Apr 28, 2021; 2(2): 10-26
Published online Apr 28, 2021. doi: 10.35712/aig.v2.i2.10
Artificial intelligence in rectal cancer
Melek Yakar, Durmus Etiz
Melek Yakar, Durmus Etiz, Department of Radiation Oncology, Eskisehir Osmangazi University Faculty of Medicine, Eskisehir 26040, Turkey
Melek Yakar, Durmus Etiz, Eskisehir Osmangazi University Center of Research and Application for Computer Aided Diagnosis and Treatment in Health, Eskisehir 26040, Turkey
Author contributions: Yakar M and Etiz D collected data and wrote the manuscript; Etiz D formatted and revised the article.
Conflict-of-interest statement: No conflict of interest has been declared by the authors.
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: Melek Yakar, MD, Assistant Professor, Department of Radiation Oncology, Eskisehir Osmangazi University Faculty of Medicine, No. 4 Odunpazari, Eskisehir 26040, Turkey. mcakcay@ogu.edu.tr
Received: January 23, 2021
Peer-review started: January 23, 2021
First decision: February 10, 2021
Revised: March 3, 2021
Accepted: March 15, 2021
Article in press: March 15, 2021
Published online: April 28, 2021
Processing time: 91 Days and 15 Hours
Abstract

Accurate and rapid diagnosis is essential for correct treatment in rectal cancer. Determining the optimal treatment plan for a patient with rectal cancer is a complex process, and the oncological results and toxicity are not the same in every patient with the same treatment at the same stage. In recent years, the increasing interest in artificial intelligence in all fields of science has also led to the development of innovative tools in oncology. Artificial intelligence studies have increased in many steps from diagnosis to follow-up in rectal cancer. It is thought that artificial intelligence will provide convenience in many ways from personalized treatment to reducing the workload of the physician. Prediction algorithms can be standardized by sharing data between centers, diversifying data, and creating big data.

Keywords: Rectal cancer; Artificial intelligence; Deep learning; Machine learning

Core Tip: There is a growing interest in the application of artificial intelligence in healthcare to improve disease diagnosis, management, and the development of effective treatments. Considering the large number of patients diagnosed with rectum cancer and a significant amount of data, artificial intelligence is an important tool to improve diagnosis and treatment, follow-up in rectal cancer, develop personalized medicine, improve the quality of life of patients, and reduce unnecessary health expenses.