Clinical & Experimental Cardiology

Clinical & Experimental Cardiology
Open Access

ISSN: 2155-9880

+44 1300 500008

Tripti R Kulkarni

Department of Electronics & Communication, Dayananda Sagar Academy of Technology and Management, Bengaluru, India

  • Research Article   
    Noninvasive method for Heart Disease prediction using Machine Learning algorithms for Photoplethysmograph signals
    Author(s): Tripti R Kulkarni* and Dushyanth ND

    Heart is a very crucial body organ that maintains and conjugates the blood in our body. In a report from WHO, one of the most significant causes of mortality today is Heart disease. Symptoms of a Heart disease include abnormal heartbeat, shortness of breath, pain in the chest, back or neck, fatigue and anxiety. If diagnosed well in advance, a lot of lives can be saved. In the proposed model we try to predict Heart Diseases in a patient using Machine Learning (ML). Various ML algorithms such as support vector classifiers, KNN, decision tree are being employed. Different ML Algorithms are used and accuracy is compared among them.. View More»

    Abstract PDF