Predicting coronary artery disease: a comparison between two data mining algorithms.

Journal: BMC public health

Published Date: Apr 29, 2019

Abstract

BACKGROUND: Cardiovascular diseases (CADs) are the first leading cause of death across the world. World Health Organization has estimated that morality rate caused by heart diseases will mount to 23 million cases by 2030. Hence, the use of data mining algorithms could be useful in predicting coronary artery diseases. Therefore, the present study aimed to compare the positive predictive value (PPV) of CAD using artificial neural network (ANN) and SVM algorithms and their distinction in terms of predicting CAD in the selected hospitals.

Authors

Haleh Ayatollahi

Health Management and Economics Research Center, Iran University of Medical Sciences, Tehran, Iran.
Leila Gholamhosseini

Department of Health Information Management, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran. gholamhosseini.l@tak.iums.ac.ir.
Masoud Salehi

Nutritional Sciences Research Center, Department of Biostatistics, School of Public Health, Iran University of Medical Sciences, Tehran, Iran.

Keywords

Age Factors Algorithms Coronary Artery Disease Data Mining Electronic Health Records Female Humans Male Middle Aged Neural Networks, Computer Predictive Value of Tests Risk Factors ROC Curve Sex Factors Socioeconomic Factors Support Vector Machine

External Resources

View on PubMed Access via DOI PubMed (31035958)

Predicting coronary artery disease: a comparison between two data mining algorithms.

Abstract

Authors

Keywords

External Resources

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