Machine learning classification techniques for heart disease prediction: a review

  • Authors

    • Maryam I. Al-Janabi
    • Mahmoud H. Qutqut
    • Mohammad Hijjawi
    https://doi.org/10.14419/ijet.v7i4.28646
  • Heart Disease, Heart Disease Diagnosis, Heart Disease Prediction, Machine Learning, Machine Learning Classification Techniques.

  • Abstract

    The most crucial task in the healthcare field is disease diagnosis. If a disease is diagnosed early, many lives can be saved. Machine learning classification techniques can significantly benefit the medical field by providing an accurate and quick diagnosis of diseases. Hence, save time for both doctors and patients. As heart disease is the number one killer in the world today, it becomes one of the most difficult diseases to diagnose. In this paper, we provide a survey of the machine learning classification techniques that have been proposed to help healthcare professionals in diagnosing heart disease. We start by overviewing the machine learning and de-scribing brief definitions of the most commonly used classification techniques to diagnose heart disease. Then, we review represent-able research works on using machine learning classification techniques in this field. Also, a detailed tabular comparison of the sur-veyed papers is presented.

     

     


     

     

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  • How to Cite

    I. Al-Janabi, M., H. Qutqut, M., & Hijjawi, M. (2018). Machine learning classification techniques for heart disease prediction: a review. International Journal of Engineering & Technology, 7(4), 5558-5564. https://doi.org/10.14419/ijet.v7i4.28646

    Received date: 2019-03-28

    Accepted date: 2019-03-28