Fuzzy classifiers in cardiovascular disease diagnostics: Review

Abstract

The complexity of biological objects makes the development of computerized medical systems a difficult algorithmic decision due to the natural uncertainty inherent in these objects. Human thinking is based on vague and approximate data that can be analyzed to form clear decisions. An exact mathematical model of biological objects may not exist in practice, or such a model may be too complex to implement. In this case, fuzzy logic is a suitable tool for solving the specified problem. The problem of medical diagnosis can be viewed as a classification problem. The article presents a literature review of the use of fuzzy classifiers in diagnostics of cardiovascular diseases. The main advantage of fuzzy classifiers in comparison with other artificial intelligence methods is the ability to interpret the resulting classification result. The review aims to expand the knowledge of various researchers working in the field of medical diagnostics.