Fuzzy cardiovascular diagnosis system using clinical data

Over the years, the use of artificial intelligence methods in medical analysis has flourished with the development of diagnostic tests and medical knowledge. Thus, the techniques of classification and detection have made much progress towards offering to medical experts and the doctors, organized and hierarchical systems to provide them with more information and knowledge for their daily function. Diagnostic assistance or diagnostic aid is an important tool for identifying abnormalities such as heart diseases. Having an appropriate model to increase the accuracy of the system, even in cases where inputs are generally low, is necessary. This paper aims to set up a medical diagnostic support system for the early detection of heart diseases, depending on cardiovascular risk factors to determine different clinical parameters useful for diagnosis. The validation of the suggested method is made using the sensitivity and specificity measures.