The aim of the study was to conceptualize the feature space characterizing the clinical features of the progressing Duchenne muscular dystrophy. The research material consisted of descriptions of the clinical picture of the disease at various stages of its progression, the analysis, correction, and structuring of which were conducted through sequential discussions between an expert and cognitologist. Knowledge engineering and fuzzy logic were used as methods. This resulted in refined descriptions of features characterizing individual disease stages. Certainty factors for features reflect the expert’s degree of trust in the frequency of occurrence of features at different stages of the disease, the difficulty of assessing the severity of a feature by a neurologist, and the difficulty of performing tests by the child. Conclusions: Structured descriptions of features characterize uniqueness of each stage of the pathological process. Certainty factors, which enable the objectification of fuzzy manifestations of features, can be used in constructing a knowledge base for a intelligent diagnostic staging system for Duchenne disease.
EDN: HDICMI
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Kobrinsky, B., Vlodavets, D., Korobkin, G., Nikolaev, A. Knowledge conceptualization and expert evaluation of the features of progressing Duchenne muscle dystrophy // Proceeding of the Institute for Systems Analysis of the Russian Academy of Science, 2026, volume 76, № 2, pp. 28–36. https://doi.org/10.14357/20790279260203