Development of an intelligent diagnostic model for pulmonological diseases based on fuzzy logic

Abstract: This article explores an approach to automating the diagnosis of pulmonary diseases using clinical decision support systems (CDSS) based on fuzzy logic methods. Both domestic and international solutions in this area are analyzed, and key devel-opment directions are identified. A patient model and a health status control system architecture are presented. An intelligent system is implemented to estimate the likelihood of a diagnosis based on symptoms. The study employs a fuzzy inference method to adapt the models to clinical data. The significance of symptoms is analyzed using Spearman rank correlation coeffi-cients. The results obtained demonstrate the effectiveness of applying fuzzy logic in medical diagnostics.

Keywords: pulmonology, fuzzy logic, spvr, patient model, diagnosis, treatment recommendations, patient condition management sys-tem

For citation:
Dubinin N. M., Gandzha T. V., Kochergin M. I., Filinyuk O. V., Dmitriev V. M. Development of an intelligent diagnostic model for pulmonological diseases based on fuzzy logic. Doklady Tomskogo gosudarstvennogo universiteta sistem upravleniya i radioelektroniki, 2025, vol. 28, no. 2, pp. 137–144. DOI: 10.21293/1818-0442-2025-28-2-137-144