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- Title
The Histological Detection of Ulcerative Colitis Using a No-Code Artificial Intelligence Model.
- Authors
Hamamoto, Yuichiro; Kawamura, Michihiro; Uchida, Hiroki; Hiramatsu, Kazuhiro; Katori, Chiaki; Asai, Hinako; Shimizu, Shigeki; Egawa, Satoshi; Yoshida, Kyotaro
- 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.
- Publication
International Journal of Surgical Pathology, 2024, Vol 32, Issue 5, p890
- ISSN
1066-8969
- Publication type
Article
- DOI
10.1177/10668969231204955