ICTACT Journal on Soft Computing

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An Effective Heart Disease Prediction Using Machine Learning Technique


Affiliations
1 Department of Information Technology, Sona College of Technology, India
     

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Heart disease is the foremost significant causes of transience within the world nowadays. It is a vital challenge to predict the cardiovascular disease in the range of clinical data investigation. Machine Learning (ML) is the most popular and powerful approach that has been appeared to be effective in making decisions and predictions from the huge amount of information delivered by the healthcare industry. ML techniques are also used in recent developments in wide areas of the Internet of Things (IoT). There are various studies done to predict the heart disease with ML techniques and it gives only a glimpse of it. In this paper, a simple TensorFlow model is proposed to find out major features by applying ML techniques that result in better accuracy in the prediction of cardiovascular disease. The prediction model is presented with diverse combinations of features and known classification algorithms. This version for coronary heart disorder with the ML based TensorFlow Model produces a more desirable overall performance with a higher accuracy stage in prediction.

Keywords

Machine Learning, Heart Disease Prediction, Feature Selection, Binary Classification, Tensorflow.
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  • An Effective Heart Disease Prediction Using Machine Learning Technique

Abstract Views: 204  |  PDF Views: 1

Authors

D. Komalavalli
Department of Information Technology, Sona College of Technology, India
R. Sangeethapriya
Department of Information Technology, Sona College of Technology, India
R. Indhu
Department of Information Technology, Sona College of Technology, India
N. Kanimozhi
Department of Information Technology, Sona College of Technology, India
G. Kasthuri
Department of Information Technology, Sona College of Technology, India

Abstract


Heart disease is the foremost significant causes of transience within the world nowadays. It is a vital challenge to predict the cardiovascular disease in the range of clinical data investigation. Machine Learning (ML) is the most popular and powerful approach that has been appeared to be effective in making decisions and predictions from the huge amount of information delivered by the healthcare industry. ML techniques are also used in recent developments in wide areas of the Internet of Things (IoT). There are various studies done to predict the heart disease with ML techniques and it gives only a glimpse of it. In this paper, a simple TensorFlow model is proposed to find out major features by applying ML techniques that result in better accuracy in the prediction of cardiovascular disease. The prediction model is presented with diverse combinations of features and known classification algorithms. This version for coronary heart disorder with the ML based TensorFlow Model produces a more desirable overall performance with a higher accuracy stage in prediction.

Keywords


Machine Learning, Heart Disease Prediction, Feature Selection, Binary Classification, Tensorflow.

References