Classification Techniques for Cardio-Vascular Diseases Using Supervised Machine Learning.

Journal: Medical archives (Sarajevo, Bosnia and Herzegovina)

Published Date: Feb 1, 2020

Abstract

INTRODUCTION: The World Health Organization has estimated that 12 million deaths occur worldwide, every year due to Heart diseases. Half the deaths in the developed countries are due to cardiovascular diseases. The early prognosis of cardiovascular diseases can aid in making decisions on lifestyle changes in high risk patients.

Authors

John Minou

Health Informatics Laboratory, Faculty of Nursing, National and Kapodistrian University of Athens, Greece.
John Mantas

Health Informatics Laboratory, Faculty of Nursing, National and Kapodistrian University of Athens, Greece.
Flora Malamateniou

Department of Digital Systems, University of Piraeus, Greece.
Daphne Kaitelidou

Department of Health Sciences, Faculty of Nursing, National and Kapodistrian University of Athens, Greece.

Keywords

Adult Aged Aged, 80 and over Cardiovascular Diseases Diagnostic Techniques, Cardiovascular Female Humans Male Middle Aged Supervised Machine Learning Terminology as Topic

External Resources

View on PubMed Access via DOI PubMed (32317833)

Classification Techniques for Cardio-Vascular Diseases Using Supervised Machine Learning.

Abstract

Authors

Keywords

External Resources

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