Extraction and structuring of expert knowledge for a diagnostic system for acute appendicitis in children
- Authors: Bogatikovа M.I.1, Kobrinsky B.A.2
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Affiliations:
- Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences
- Federal Research Center "Computer Science and Control" of Russian Academy of Sciences
- Issue: Vol 75, No 1 (2025)
- Pages: 3-9
- Section: Data Mining and Pattern Recognition
- URL: https://journals.rcsi.science/2079-0279/article/view/317017
- DOI: https://doi.org/10.14357/20790279250101
- EDN: https://elibrary.ru/ZVHAAA
- ID: 317017
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Abstract
The article presents the process of knowledge extraction and structuring in the medical subject area for the created expert system for diagnosing acute appendicitis. Knowledge was elicited from two experts. Difficulties in the formation of the feature space, which is necessary to determine the form of appendicitis, complications and differential diagnostics with other diseases similar in clinical picture, are noted. A key feature of the structured knowledge representation is, along with the attribute, characteristic and value of the feature, the inclusion of an "index sign" position, which indicates the stage of the pathological process or a possible diagnosis from the differential diagnostic range of acute appendicitis.
About the authors
M. I. Bogatikovа
Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences
Email: marya-00@list.ru
Assistant 44/2 Vavilova str., Moscow, 119333
B. A. Kobrinsky
Federal Research Center "Computer Science and Control" of Russian Academy of Sciences
Email: kba_05@mail.ru
Professor, Doctor of medical sciences 44/2 Vavilova str., Moscow, 119333
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