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Knowledge-Based Diagnostic System With a Precedent Libraryстатья
Информация о цитировании статьи получена из
Scopus
Дата последнего поиска статьи во внешних источниках: 1 октября 2025 г.
- Авторы: Blagosklonov Nikolay, Gribova Valeriya, Kobrinskii Boris, Shalfeeva Elena
- Сборник: Lecture Notes in Computer Science
- Серия: 12948
- Год издания: 2021
- Издательство: Springer International Publishing AG
- Местоположение издательства: Cham, Switzerland
- Первая страница: 289
- Последняя страница: 302
- DOI: 10.1007/978-3-030-86855-0_20
- Аннотация: The hypothesis of the presumptive diagnosis before laboratory confirmation is especially important in orphan (rare) hereditary diseases. It is possible to solve this problem using computer-based decision support systems based on knowledge. However, in medical practice, there are cases of an atypical clinical picture in patients with fuzzy manifestations of features. In such cases, it is possible to increase the diagnostic accuracy using a precedent approach. The concept of “synthetic precedent” is introduced, which is the result of the transformation of an atypical case into a synthesized description. The paper presents methods for constructing synthetic precedents of two types. The precedents of the first type are created as a result of extension with the fuzzy boundaries for ordinal variables. The precedents of the second type are received by softening the requirement for the number of necessary signs of a patient to match an atypical case from the precedent library. An approach to the creation of a hybrid system, including a traditional knowledge base and a precedent library, is proposed and demonstrated. The use of the hybrid system increases the accuracy of early diagnosis of orphan diseases in childhood.
- Добавил в систему: Кобринский Борис Аркадьевич