Heart disease in Python

Abstract:

Cardiovascular disease is one of the most heinous disease, especially the silent heart attack, which attacks a person so abruptly that there’s no time to get it treated and such disease is very difficult to be diagnosed. The lack of specialist doctors and increase in wrong diagnosed cases has necessitated the need for building an efficient heart disease detection system. Various medical data mining and machine learning techniques are being implemented to extract the valuable information regarding the heart disease prediction. Yet, the accuracy of the desired results are not satisfactory. This paper proposes a heart attack prediction system using Deep learning techniques, specifically Recurrent Neural Network to predict the likely possibilities of heart related diseases of the patient. Recurrent Neural Network is a very powerful classification algorithm that makes use of Deep Learning approach in Artificial Neural Network. The paper discusses in detail the major modules of the system along with the related theory. The proposed model incorporates deep learning and data mining to provide the accurate results with minimum errors. This paper provides a direction and precedent for the development of a new breed of heart attack prediction platform.