Machine learning-based analysis and prediction of meteorological factors and urban heatstroke diseases.

Journal: Frontiers in public health
PMID: 39104885

Abstract

INTRODUCTION: Heatstroke is a serious clinical condition caused by exposure to high temperature and high humidity environment, which leads to a rapid increase of the core temperature of the body to more than 40°C, accompanied by skin burning, consciousness disorders and other organ system damage. This study aims to analyze the effect of meteorological factors on the incidence of heatstroke using machine learning, and to construct a heatstroke forecasting model to provide reference for heatstroke prevention.

Authors

  • Hui Xu
    No 202 Hospital of People's Liberation Army, Liaoning 110003, China.
  • Shufang Guo
    School of Management, Beijing University of Chinese Medicine, Beijing, China.
  • Xiaojun Shi
    Department of Hepatology, The 4th People's Hospital of Qinghai Province, Xining, Qinghai, China.
  • Yanzhen Wu
    Inner Mongolia Medical University, Huhehot Xinhua Street, Inner Mongolia, 010059, China. Electronic address: 253706468@qq.com.
  • Junyi Pan
    School of Management, Beijing University of Chinese Medicine, Beijing, China.
  • Han Gao
    Zhejiang Construction Investment Environment Engineering Co, Ltd., Hangzhou, 310013, PR China.
  • Yan Tang
  • Aiqing Han
    School of Management, Beijing University of Chinese Medicine, Beijing, China.

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