International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 181 - Number 17 |
Year of Publication: 2018 |
Authors: Ankita Naik, Nitesh Naik |
10.5120/ijca2018917765 |
Ankita Naik, Nitesh Naik . Prognosis of Heart Disease using Data Mining Techniques: A Comprehensive Survey. International Journal of Computer Applications. 181, 17 ( Sep 2018), 14-18. DOI=10.5120/ijca2018917765
Prediction and diagnosis of heart disease has become a formidable factor faced by medical practitioners and hospitals both in India and also worldwide. The early and timely diagnosis of heart disease plays a very crucial role in halting its advancement and reducing related medical costs. Taking into account the ever-increasing rise in heart disease-induced mortality, different techniques have been adopted to treat it. The idea intends to develop a heart disease prediction model, which will implement ensemble techniques, can help the doctors in detecting the heart disease status based on the patient's clinical data. This paper provides a quick and facile analysis and understanding of available prediction models using data mining from 2011 to 2017. The comparison shows the accuracy level of each model given by different researchers.