DECISION SUPPORT SYSTEM BASED ON SIGNS AND SYMPTOMS USING NEURAL NETWORKS FOR CONGENITAL HEART DISEASE DIAGNOSIS

Abstract

One of the important methods of data analysis is classification. Many real-world problems in various fields, such as business, science, industry, and medicine can be solved using a classification approach. Neural networks have emerged as an important tool for classification. The advantages of neural networks help to efficiently classify these data. In this study, a set of heart disease data is analyzed using a neural network approach. To improve the efficiency of the classification process, a parallel approach was also adopted in preparation.