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©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Clin Oncol. Feb 24, 2022; 13(2): 125-134
Published online Feb 24, 2022. doi: 10.5306/wjco.v13.i2.125
Published online Feb 24, 2022. doi: 10.5306/wjco.v13.i2.125
Artificial intelligence and cholangiocarcinoma: Updates and prospects
Hossein Haghbin, Department of Gastroenterology, Ascension Providence Southfield, Southfield, MI 48075, United States
Muhammad Aziz, Department of Gastroenterology, University of Toledo Medical Center, Toledo, OH 43614, United States
Author contributions: Haghbin H and Aziz M designed and performed the research study. Haghbin H and Aziz M wrote the manuscript; all authors have read and approved the final manuscript.
Conflict-of-interest statement: Authors have no conflict of interest.
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: Hossein Haghbin, MD, Doctor, Department of Gastroenterology, Ascension Providence Southfield, 16001 W Nine Mile Road, Southfield, MI 48075, United States. hoshaq@yahoo.com
Received: November 9, 2021
Peer-review started: November 9, 2021
First decision: December 27, 2021
Revised: January 9, 2022
Accepted: January 25, 2022
Article in press: January 25, 2022
Published online: February 24, 2022
Processing time: 106 Days and 8.6 Hours
Peer-review started: November 9, 2021
First decision: December 27, 2021
Revised: January 9, 2022
Accepted: January 25, 2022
Article in press: January 25, 2022
Published online: February 24, 2022
Processing time: 106 Days and 8.6 Hours
Core Tip
Core Tip: The wide array of modalities available to treat cholangiocarcinoma (CCA) in addition to the diversity of the tumor urges us to use individualized therapy. To establish the proper approach to diagnose, treat, and prognose CCA, analysis of available data is the key to achieve the individualized care. Artificial intelligence can be a potential modality for achieving this goal.