Intelligent health risk prediction systems using machine learning: a review

  • Authors

    • Mr Santosh A. Shinde KLEF
    • Dr P. Raja Rajeswari KLEF
    2018-06-23
    https://doi.org/10.14419/ijet.v7i3.12654
  • Electronic Health Records, Health Risk Prediction, Machine Learning, Risk Prediction Model.

  • Abstract

    Humans are considered to be the most intelligent species on the mother earth and are inherently more health conscious. Since Centuries mankind has discovered various proven healthcare systems. To automate the process and predict diseases more accurately machine learning methods are gaining popularity in research community. Machine Learning methods facilitate development of the intelligence into a machine, so that it can perform better in the future using the learned experience. Machine learning methods application on electronic health record dataset could provide valuable information and predication of health risks.

    The aim of this research review paper are four-fold: i) serve as a guideline for researchers who are new to machine learning area and want to contribute to it, ii) provide state-of-the-art survey of machine learning, iii) application of machine learning techniques in the health prediction, and iv) provides further research directions required into health prediction system using machine learning.

     

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  • How to Cite

    Santosh A. Shinde, M., & P. Raja Rajeswari, D. (2018). Intelligent health risk prediction systems using machine learning: a review. International Journal of Engineering & Technology, 7(3), 1019-1023. https://doi.org/10.14419/ijet.v7i3.12654

    Received date: 2018-05-10

    Accepted date: 2018-06-01

    Published date: 2018-06-23