Artificial intelligence systems in medicine allow for the effective solution of various problems, in particular those related to the identification of factors threatening the development of diseases. Prevention and early diagnosis of chronic tonsillitis remains one of the leading problems of otorhinolaryngology. Inflammation of the tonsils, including chronic tonsillitis, can lead to various complications, including systemic diseases. This determines the importance of preventive measures that take into account the presence of threatening factors at the pre-nosological stage. In the article discusses the problem of expert assessment of controlled risk factors for the development of chronic tonsillitis, their objective characteristics, taking into account possible uncertainty. Due to this purpose, a representation of factors with their characteristics, accompanied by corresponding numerical values, is introduced. Each characteristic is accompanied by an expert assessment of the risk level, which is an original solution for artificial intelligence systems. On this basis, a questionnaire with alternative answers has been constructed, including current risk factors for the development of chronic tonsillitis. Structured indicators - disease predictors - form a knowledge field of risk factors for chronic tonsillitis, which will serve as the knowledge base for an intelligent recommendation system.
DOI: 10.22204/2410-4639-2026-129-01-64-75
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Vladimir Belov, Boris Kobrinsky, Anna Akimova. Expert Approach to Forming the Signal Space of Chronic Tonsillitis Risk Factors in Children // RFBR Bulletin № 1(129), 2026, pp. 64–75.