Abstract
Diagnosing heart disease is a challenging process for physicians. Insufficient number of experts, late diagnosis and misdiagnosis are the difficulties in this process. To overcome these difficulties, systems based on artificial intelligence are used today. Appropriate system selection and obtaining sufficient data sets are a challenge for researchers. In this study, a high-performance CAD architecture was proposed for the detection of heart disease. The proposed architecture has shown a higher performance than the studies carried out using the UCI dataset in the literature.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have