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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| Format: | Article |
| Language: | English |
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Nature Publishing Group
2021-07-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-021-24823-0 |
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doaj-eabce182db884c9da55d3f0e13addb3e2021-08-01T11:38:11ZengNature Publishing GroupNature Communications2041-17232021-07-0112111110.1038/s41467-021-24823-0Heatstroke predictions by machine learning, weather information, and an all-population registry for 12-hour heatstroke alertsSoshiro Ogata0Misa Takegami1Taira Ozaki2Takahiro Nakashima3Daisuke Onozuka4Shunsuke Murata5Yuriko Nakaoku6Koyu Suzuki7Akihito Hagihara8Teruo Noguchi9Koji Iihara10Keiichi Kitazume11Tohru Morioka12Shin Yamazaki13Takahiro Yoshida14Yoshiki Yamagata15Kunihiro Nishimura16Department of Preventive Medicine and Epidemiology, National Cerebral and Cardiovascular CenterDepartment of Preventive Medicine and Epidemiology, National Cerebral and Cardiovascular CenterDepartment of Civil, Environmental and Applied Systems Engineering, Faculty of Environmental and Urban Engineering, Kansai UniversityDepartment of Preventive Medicine and Epidemiology, National Cerebral and Cardiovascular CenterDepartment of Preventive Medicine and Epidemiology, National Cerebral and Cardiovascular CenterDepartment of Preventive Medicine and Epidemiology, National Cerebral and Cardiovascular CenterDepartment of Preventive Medicine and Epidemiology, National Cerebral and Cardiovascular CenterDepartment of Preventive Medicine and Epidemiology, National Cerebral and Cardiovascular CenterDepartment of Preventive Medicine and Epidemiology, National Cerebral and Cardiovascular CenterDepartment of Cardiovascular Medicine, National Cerebral and Cardiovascular CenterDirector General, National Cerebral and Cardiovascular Center HospitalDepartment of Civil, Environmental and Applied Systems Engineering, Faculty of Environmental and Urban Engineering, Kansai UniversityDepartment of Civil, Environmental and Applied Systems Engineering, Faculty of Environmental and Urban Engineering, Kansai UniversityHealth and Environmental Risk Division, National Institute for Environmental StudiesEarth System Division, National Institute for Environmental StudiesEarth System Division, National Institute for Environmental StudiesDepartment of Preventive Medicine and Epidemiology, National Cerebral and Cardiovascular CenterIn 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.https://doi.org/10.1038/s41467-021-24823-0 |
| collection |
DOAJ |
| language |
English |
| format |
Article |
| sources |
DOAJ |
| author |
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 |
| spellingShingle |
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 Heatstroke predictions by machine learning, weather information, and an all-population registry for 12-hour heatstroke alerts Nature Communications |
| author_facet |
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 |
| author_sort |
Soshiro Ogata |
| title |
Heatstroke predictions by machine learning, weather information, and an all-population registry for 12-hour heatstroke alerts |
| title_short |
Heatstroke predictions by machine learning, weather information, and an all-population registry for 12-hour heatstroke alerts |
| title_full |
Heatstroke predictions by machine learning, weather information, and an all-population registry for 12-hour heatstroke alerts |
| title_fullStr |
Heatstroke predictions by machine learning, weather information, and an all-population registry for 12-hour heatstroke alerts |
| title_full_unstemmed |
Heatstroke predictions by machine learning, weather information, and an all-population registry for 12-hour heatstroke alerts |
| title_sort |
heatstroke predictions by machine learning, weather information, and an all-population registry for 12-hour heatstroke alerts |
| publisher |
Nature Publishing Group |
| series |
Nature Communications |
| issn |
2041-1723 |
| publishDate |
2021-07-01 |
| description |
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. |
| url |
https://doi.org/10.1038/s41467-021-24823-0 |
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