Heatstroke predictions by machine learning, weather information, and an all-population registry for 12-hour heatstroke alerts

Heatstroke predictions by machine learning, weather information, and an all-population registry for 12-hour heatstroke alerts

In the context of climate change, heatstroke is expected to become an increasingly relevant public health concern. Here, the authors develop and validate prediction models for the number of all heatstroke cases in different cities in Japan.

Bibliographic Details
Main Authors: Soshiro Ogata, Misa Takegami, Taira Ozaki, Takahiro Nakashima, Daisuke Onozuka, Shunsuke Murata, Yuriko Nakaoku, Koyu Suzuki, Akihito Hagihara, Teruo Noguchi, Koji Iihara, Keiichi Kitazume, Tohru Morioka, Shin Yamazaki, Takahiro Yoshida, Yoshiki Yamagata, Kunihiro Nishimura
Format: Article
Language:English
Published: Nature Publishing Group 2021-07-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-021-24823-0

Internet

https://doi.org/10.1038/s41467-021-24823-0

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