Evidence Review
Copyright ©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.
Artif Intell Cancer. Sep 8, 2023; 4(1): 1-10
Published online Sep 8, 2023. doi: 10.35713/aic.v4.i1.1
Artificial intelligence in the diagnosis of thyroid cancer: Recent advances and future directions
Lakshmi Nagendra, Joseph M Pappachan, Cornelius James Fernandez
Lakshmi Nagendra, Department of Endocrinology, JSS Medical College & JSS Academy of Higher Education and Research Center, Mysore 570015, India
Joseph M Pappachan, Department of Endocrinology & Metabolism, Lancashire Teaching Hospitals NHS Trust, Preston PR2 9HT, United Kingdom
Joseph M Pappachan, Faculty of Science, Manchester Metropolitan University, Manchester M15 6BH, M15 6BH, United Kingdom
Joseph M Pappachan, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester M13 9PL, United Kingdom
Cornelius James Fernandez, Department of Endocrinology & Metabolism, Pilgrim Hospital, United Lincolnshire Hospitals NHS Trust, PE21 9QS PE21 9QS, United Kingdom
Author contributions: Nagendra L performed the literature search, interpreted the relevant literature, and drafted the initial manuscript; Pappachan JM and Fernandez CJ conceived the idea and provided additional input to design the paper; Nagendra L and Fernandez CJ prepared the figures and with additional input from Pappachan JM, revised the article critically for important intellectual content after peer reviews; All authors have read and approved the final version of the manuscript.
Conflict-of-interest statement: There are no conflicts on interest among 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: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Joseph M Pappachan, FRCP, MD, Academic Editor, Professor, Senior Researcher, Department of Endocrinology & Metabolism, Lancashire Teaching Hospitals NHS Trust, Sharoe Green Lane, Preston PR2 9HT, United Kingdom. drpappachan@yahoo.co.in
Received: June 3, 2023
Peer-review started: June 3, 2023
First decision: July 4, 2023
Revised: July 24, 2023
Accepted: August 7, 2023
Article in press: August 7, 2023
Published online: September 8, 2023
Processing time: 95 Days and 15.6 Hours
Core Tip

Core Tip: In its broadest sense artificial intelligence (AI) is the ability of machines to approach problem-solving with human-like logic. Thyroid cancer is the most common endocrine malignancy with increasing incidence rates, but with stable lower mortality rates. As in the other domains of healthcare, AI is now revolutionising the diagnosis, management, and prognostication of thyroid cancer. In this evidence-based review we update the recent advances in AI-based techniques for the management of thyroid cancer.