Implementation of Artificial Fish Swarm Optimization for Cardiovascular Heart Disease

Today we are living in the digital world, with a systematic life, which may leads to many new diseases due to artificial production on agriculture, mental stress, economic and social stress too. Due to machine world, patients hearts diseases can be predict by various heart diseases detection model. There are various techniques, models and tools are predicted to find the real status of heart diseases which may have advantages and disadvantages too. This paper will try to improve the performance of the new proposed techniques which is used to determine the drawback from the existing system and overcome the drawback. The proposed techniques is used to preprocess the information and moved to the next process of selection to determine accuracy, sensitivity, specificity, precision, recall and F-measure from the dataset retrieved from three major metropolitan cities likes Chennai, Bangalore and Delhi. These proposed techniques provide the more efficient and effective with the existing system with 90% to 95%.