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Publikacje Pracowników Politechniki Lubelskiej

MNiSW
20
Lista 2023
Status:
Autorzy: Wójcik Waldemar, Mezhiievska Iryna, Pavlov Sergii V., Lewandowski Tomasz, Vlasenko Oleg, Maslovskyi Valentyn, Volosovych Oleksandr, Kobylianska Iryna M., Moskovchuk Olha, Ovcharuk Vasyl, Lewandowska Anna
Dyscypliny:
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Rok wydania: 2023
Wersja dokumentu: Elektroniczna
Język: angielski
Numer czasopisma: 2
Wolumen/Tom: 20
Numer artykułu: 979
Strony: 1 - 18
Web of Science® Times Cited: 1
Scopus® Cytowania: 5
Bazy: Web of Science | Scopus
Efekt badań statutowych NIE
Finansowanie: Funded by the Faculty of Electrical Engineering and Computer Science, Lublin University of Technology
Materiał konferencyjny: NIE
Publikacja OA: TAK
Licencja:
Sposób udostępnienia: Witryna wydawcy
Wersja tekstu: Ostateczna wersja opublikowana
Czas opublikowania: W momencie opublikowania
Data opublikowania w OA: 5 stycznia 2023
Abstrakty: angielski
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.