ECG based Decision Support System for Clinical Management using Machine Learning Techniques. Issue 1 (February 2021)

• Record Type: Journal Article
• Authors: Moturi, Sireesha; Vemuru, Srikanth; Tirumala Rao, S. N.
• Is Part Of: IOP conference series. Volume 1085:Issue 1(2021)
• Publication Date: 2021-02
• Subjects: Materials science -- Periodicals; 620.1105
• DOI: 10.1088/1757-899X/1085/1/012016
• Languages: English
• ISSNs: 1757-8981

Abstract

Abstract: Heart disease prediction system using ECG is to predict heart disease using ECG signals. Heart is the next major organ comparing to brain, which has more priority in human body. Heart disease diagnosis is a complex task which requires much experience and knowledge. The huge amount of data generated for prediction of heart disease is too complex and voluminous to be processed by traditional methods. By using traditional methods doctors took lot of time to diagnosis the disease. So, an entropy based feature selection technique is used with classification algorithms in order to reduce the search space. The proposed model was tested on the real time dataset of NRI Hospital medical data. Using this system it is easier to predict the disease. It will also helpful for the doctors to take quick decisions.