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©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved.
Artif Intell Gastroenterol. Jun 28, 2022; 3(3): 88-95
Published online Jun 28, 2022. doi: 10.35712/aig.v3.i3.88
Published online Jun 28, 2022. doi: 10.35712/aig.v3.i3.88
Artificial intelligence using advanced imaging techniques and cholangiocarcinoma: Recent advances and future direction
Aaron R Brenner, Patrick J Carey, Danielle Joiner, Department of Internal Medicine, University of Kentucky College of Medicine, Lexington, KY 40536, United States
Passisd Laoveeravat, Division of Digestive Diseases and Nutrition, University of Kentucky College of Medicine, Lexington, KY 40536, United States
Samuel H Mardini, Division of Digestive Diseases and Nutrition, University of Kentucky College of Medicine, Lexington, KENTUCKY 40536, United States
Manol Jovani, Digestive Diseases and Nutrition, University of Kentucky Albert B. Chandler Hospital, Lexington, KY 40536, United States
Author contributions: All authors contributed to the paper with regard to conception and design of the study, literature review and analysis, drafting the manuscript and all authors approved the final version of the manuscript.
Conflict-of-interest statement: The authors declare that they 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: Manol Jovani, MD, MSc, Assistant Professor, Attending Doctor, Doctor, Digestive Diseases and Nutrition, University of Kentucky Albert B. Chandler Hospital, 770 Rose St Room MN662, Lexington, KY 40536, United States. manol.jovani@mail.harvard.edu
Received: March 7, 2022
Peer-review started: March 7, 2022
First decision: April 10, 2022
Revised: April 16, 2022
Accepted: May 5, 2022
Article in press: May 5, 2022
Published online: June 28, 2022
Processing time: 113 Days and 5.6 Hours
Peer-review started: March 7, 2022
First decision: April 10, 2022
Revised: April 16, 2022
Accepted: May 5, 2022
Article in press: May 5, 2022
Published online: June 28, 2022
Processing time: 113 Days and 5.6 Hours
Core Tip
Core Tip: Artificial intelligence (AI) aided by multiple imaging modalities is accurate and effective for diagnosis and characterization of biliary masses. The advancement and incorporation of imaging into artificial intelligence will help to decrease delay in diagnosis of cholangiocarcinoma and potentially decrease mortality. This review examines studies showing that AI can assist in real-time diagnosis of cholangiocarcinoma and predict outcomes of treatment. Current data suggests that AI will soon become an indispensable part of the armamentarium for the management of cholangiocarcinoma and other biliary diseases.