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Research Article

Engineering and Technology Research 5(4): 066-074, July2022
DOI: 10.15413/etr.2022.108

ISSN: 2682 5716
2022 Academia Publishing



Diagnosis of cardiovascular diseases using classification algorithms

Accepted 21st May, 2022


Mehmet Akif Tanisik and Emine Yaman*

Department of Computer Science and Engineering, International University of Sarajevo, Sarajevo, Bosnia and Herzegovina.

*Corresponding author. E-mail: eyaman@ius.edu.ba.

Heart diseases are the most common diseases in the world, and it will continue to be the leading cause of death for a long time. Each year 17.9 million people die due to cardiovascular diseases (CVDs) which means an estimated 32% of all deaths worldwide. However, many of the heart disease factors are preventable or treatable. If these factors are prevented or treated, it is a good opportunity to reduce the loss of life as a result of heart diseases. At present, data science is actively used by people and the importance of data science is increasing daily. It is an important fact for humanity that heart diseases and similar medical problems can be predicted using data science. For this reason, early detection of the disease is aimed with the studies carried out by applying statistical methods in the field of medicine. This research determines the relationship between heart diseases and other characteristics of the human body to early diagnosis of heart diseases. In this research, data mining approaches were used and different data science algorithms were applied to predict the heart diseases of patients. Nave Bayes, Logistic Regression, Multilayer Perceptron and Random Forest algorithms were used for the classification and diagnosis of cardiovascular diseases prediction done. Nave Bayes algorithm had accuracy of 88.52%. Thus, the accuracy of Nave Bayes is the best accuracy among all other algorithms.

Key words: Heart disease prediction, Nave Bayes, logistic regression, random forest, machine learning, classification.

Cite this article as:
Tanisik MA, Yaman E (2022). Diagnosis of cardiovascular diseases using classification algorithms. Eng. Technol. Res. 5(4): 066-074.

This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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