Abstract
The article solves the problem of creating a software package for computer diagnostics of gastritis. The patient examination indicators and their diagnoses are used as input data. To successfully solve this problem, a logical approach to data analysis is being developed, which allows us to find the patterns necessary for high-quality diagnostics. These laws are identified based on the data provided by specialists and include the results of patient examinations and the existing experience in medical practice in making a diagnosis. Systems of multivalued predicate logic are used for expressive data representation. An algorithm is proposed that implements and simplifies the approaches under consideration. As a result, the developed software package selects the most suitable types of the disease with a predetermined accuracy based on the data of patient diagnostics. If it is not possible to make a diagnosis with a given accuracy based on the results of the examination, then either the accuracy of the decision changes, or it is proposed to undergo an additional examination.
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Lyutikova, L.A. (2022). Data Mining for Solving Medical Diagnostics Problems. In: Suma, V., Fernando, X., Du, KL., Wang, H. (eds) Evolutionary Computing and Mobile Sustainable Networks. Lecture Notes on Data Engineering and Communications Technologies, vol 116. Springer, Singapore. https://doi.org/10.1007/978-981-16-9605-3_15
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