Health Monitoring Using Machine Learning

Authors

  • Hari Priya P B
  • Dhivya Shree K S
  • Indhumathi S
  • Saumya S
  • Thangaraj K

Keywords:

Health Monitoring System, Decision tree algorithm, Flask, Risk level.

Abstract

Good Health is one of the primary factors that a human requires to move ahead with his life. The health care system’s goal is to enhance the population in the most effective way, in the light of society’s available resources and needs. In majority of countries, the death rates are becoming high due to the lack of well-timed medical instruments and treatments. These health risks can be shut out by providing standard health care services. Our Health Monitoring System is a Web Application, which is created by using Flask framework. In this Health Monitoring System, we have used Decision Tree Classification (Supervised Machine Learning technique) for good prediction of results. Here, we have used our own dataset to train and evaluate our model. Based on that evaluation, we would be able to predict the patient’s health level and area of risk.

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Published

2021-04-20

How to Cite

Hari Priya P B, Dhivya Shree K S, Indhumathi S, Saumya S, & Thangaraj K. (2021). Health Monitoring Using Machine Learning. International Journal of Progressive Research in Science and Engineering, 2(4), 9–12. Retrieved from https://www.journals.grdpublications.com/index.php/ijprse/article/view/252

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Section

Articles