Prediction of Heart Disease Based on Data Mining Techniques
Subject Areas : International Journal of Data Envelopment Analysis
Alizadeh Mojtaba
1
*
,
Arash Moradi
2
1 - Department of Computer Engineering, Lorestan University, Khorramabad, Iran
2 - Department of Computer Engineering, Lorestan University, Khorramabad, Iran
Keywords: Machine Learning, Heart Diseases, Data Mining,
Abstract :
|
Heart disease is one of the most popular health problems for human being. According to statistics published by the World Health Organization (WHO), two main diseases that caused about a quarter of deaths all around the world in 2016, were heart disease and stroke. Although a lot of articles suggested different ways of detection and treatment of the heart and its disease, no framework is proposed to leverage the machine learning techniques to do it. We tabulate 32 articles regarding the factors such as Algorithm, Database, Feature Selection, Evaluation Measures, Performance evaluation, Efficiency, and different used tools. The same factors also are leveraged for comparison including 17 papers that focus on ECG and HRV signals. The output of this comparison leads to a classification framework. All steps from pre-processing to classification are provided in the proposed framework. This survey and the proposed framework offer a roadmap that can help researchers to conduct future researches in the field. |
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