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