Construction of fuzzy inference rules for medicine diagnostics problems
Sh F MadrakhimovDepartment of Applied Mathematics and Intellectual Technologies, National University of Uzbekistan named after Mirzo Ulugbek, 4 University Street, 100095, Tashkent, UzbekistanGulnora RozikhodjaevaKodirbek MakharovDepartment of Applied Informatics, Yeoju Technical Institute in Tashkent, 156 Usman Nasyr Street, 100121 Tashkent, Uzbekistan
ABI
Abstract
Data mining is one of the newest analytical methods that have been used to serve medical science research and has been shown to be a valid, sensitive, and reliable method to discover patterns and relationships. The article considers the possibility of using data mining techniques to search for hidden patterns in health databases for the purpose of filling the knowledge base in medical diagnostic systems. The formation of fuzzy inference rules is made on the basis of two methods for splitting the values of quantitative features in the description of objects (patients) of the sample into intervals. The methodology of using these rules is described by the example of diagnosing instability of a carotid atherosclerotic plaque.
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