Applying Machine Learning to predict Hand-Foot-Mouth disease outbreaks in Vietnam

Authors

  • Thanh Ngoc Nguyen School of Science, Engineering and Technology, RMIT University Vietnam
  • Dr Dinh Ngoc Minh School of Science, Engineering and Technology, RMIT University Vietnam

Keywords:

HFMD, machine learning, public health informatics

Abstract

Applying Machine Learning to find out the patterns of hand foot mouth diseases is critical to understand the impacts of social-natural conditions to the outbreak of the diseases. This paper uses data from Vietnam to find out what factors contribute the most to the increase of cases and what models can help to predict this increase. We identify temperature as the important factors and the Random Forest Regressor is the model that produces best results.

Published

2021-12-15

How to Cite

Nguyen, T., & Minh, D. (2021). Applying Machine Learning to predict Hand-Foot-Mouth disease outbreaks in Vietnam. Journal of Health Informatics in Developing Countries, 15(2). Retrieved from https://jhidc.org/index.php/jhidc/article/view/300

Issue

Vol. 15 No. 2 (2021)

Section

Research Articles

Copyright (c) 2021 Journal of Health Informatics in Developing Countries

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