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.

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Detalles Bibliográficos
Autores principales: 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
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
Materias:
Science
Q
Acceso en línea:https://doaj.org/article/eabce182db884c9da55d3f0e13addb3e
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Sumario: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.

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