Abstract
The features of medical diagnostics that affect the quality of decision-making in decision support systems are considered. The purpose of this article is to briefly introduce various soft computing methodologies and present various applications in medicine. Formalized expert information on the given sets of diagnoses and their symptoms. A method has been developed for generating a diagnostic inference during therapeutic examinations based on fuzzy logic. The goal is to demonstrate the possibilities of applying soft computing to problems related to medicine. A transition is made from fuzzy values to certain physical parameters that can serve as commands to the actuator. The result of fuzzy inference, of course, will be fuzzy, but for the executive device it means absolutely nothing, therefore, to eliminate fuzziness, special mathematical methods can be applied to obtain the exact values transmitted by a number of diseases directly to the performer in medical diagnostics. Fuzzy logic and fuzzy set theory is a branch of mathematics that generalizes classical logic and set theory. The fuzzy system copes with such a task very quickly, despite the fact that instead of complex differential equations, the entire process of movement is described in terms of natural language: “norm”, “average”, “high” - as if the operator controls the system. Keywords: medical diagnostics, fuzzy logic, decision support system, fuzzy systems.
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