Background: Today, cardiovascular diseases cause 47% of all deaths among the European population, which is 4 million cases every year. In Ukraine, CAD accounts for 65% of the mortality rate from circulatory system diseases of the able-bodied population and is the main cause of disability. The aim of this study is to develop a medical expert system based on fuzzy sets for assessing the degree of coronary artery lesions in patients with coronary artery disease. Methods: The method of using fuzzy sets for the implementation of an information expert system for solving the problems of medical diagnostics, in particular, when assessing the degree of anatomical lesion of the coronary arteries in patients with various forms of coronary artery disease, has been developed. Results: The paper analyses the main areas of application of mathematical methods in medical diagnostics, and formulates the principles of diagnostics, based on fuzzy logic. The developed models and algorithms of medical diagnostics are based on the ideas and principles of artificial intelligence and knowledge engineering, the theory of experiment planning, the theory of fuzzy sets and linguistic variables. The expert system is tested on real data. Through research and comparison of the results of experts and the created medical expert system, the reliability of supporting the correct decision making of the medical expert system based on fuzzy sets for assessing the degree of anatomical lesion of the coronary arteries in patients with various forms of coronary artery disease with the assessment of experts was 95%, which shows the high efficiency of decision making. Conclusions: The practical value of the work lies in the possibility of using the automated expert system for the solution of the problems of medical diagnosis based on fuzzy logic for assessing the degree of anatomical lesion of the coronary arteries in patients with various forms of coronary artery disease. The proposed concept must be further validated for inter-rater consistency and reliability. Thus, it is promising to create expert medical systems based on fuzzy sets for assessing the degree of disease pathology.

The work analyzes the world experience in the development of medical information technologies. The method of using fuzzy sets for the implementation of an information expert system for solving the problems of medical diagnostics, in particular, during assessing the degree of anatomical damage of the coronary bed in patients with various forms of coronary artery disease, has been developed. The practical value of the work lies in the possibility of using an automated expert system to solve the problems of medical diagnosis based on fuzzy logic when assessing the degree of anatomical damage of the coronary bed in patients with various forms of coronary artery disease.

The paper analyzes the main areas of application of mathematical methods in medical diagnostics, formulates principles of diagnostics based on fuzzy logic; developed mathematical models and algorithms that formalize the process of making diagnostic decisions based on fuzzy logic with quantitative and qualitative parameters of the patient's condition; developed mathematical models of membership function. Mathematical models and algorithms have been developed that formalize the process of making diagnostic decisions based on fuzzy logic with quantitative and qualitative parameters of the patient's condition; developed mathematical models of membership functions, formalizing the representation of quantitative and qualitative parameters of the patient's condition in the form of fuzzy sets, used in models and algorithms for diagnosis and finding a diagnosis of assessing the intensity of reactive postoperative edema in patients of all study groups. An expert system was implemented for solving the problems of medical diagnosis based on fuzzy logic when assessing the intensity of reactive swelling of soft tissues, which develops in the postoperative period in patients of all study groups against the background of diabetes. The paper analyzes the main areas of application of mathematical methods in medical diagnostics, formulates the principles of diagnostics based on fuzzy logic.