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The Histological Detection of Ulcerative Colitis Using a No-Code Artificial Intelligence Model.

Authors :
Hamamoto Y
Kawamura M
Uchida H
Hiramatsu K
Katori C
Asai H
Shimizu S
Egawa S
Yoshida K
Source :
International journal of surgical pathology [Int J Surg Pathol] 2024 Aug; Vol. 32 (5), pp. 890-894. Date of Electronic Publication: 2023 Oct 25.
Publication Year :
2024

Abstract

Ulcerative colitis (UC) is an intractable disease that affects young adults. Histological findings are essential for its diagnosis; however, the number of diagnostic pathologists is limited. Herein, we used a no-code artificial intelligence (AI) platform "Teachable Machine" to train a model that could distinguish between histological images of UC, non-UC coloproctitis, adenocarcinoma, and control. A total of 5100 histological images for training and 900 histological images for testing were prepared by pathologists. Our model showed accuracies of 0.99, 1.00, 0.99, and 0.99, for UC, non-UC coloproctitis, adenocarcinoma, and control, respectively. This is the first report in which a no-code easy AI platform has been able to comprehensively recognize the distinctive histologic patterns of UC.<br />Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Details

Language :
English
ISSN :
1940-2465
Volume :
32
Issue :
5
Database :
MEDLINE
Journal :
International journal of surgical pathology
Publication Type :
Academic Journal
Accession number :
37880949
Full Text :
https://doi.org/10.1177/10668969231204955