Effects of heatwave features on machine-learning-based heat-related ambulance calls prediction models in Japan.

Ke, Deng; Takahashi, Kiyoshi; Takakura, Jun'ya; Takara, Kaoru; Kamranzad, Bahareh

Ke, Deng; Takahashi, Kiyoshi; Takakura, Jun'ya; Takara, Kaoru; Kamranzad, Bahareh.

Afiliação

Ke D; Graduate School of Advanced Integrated Studies in Human Survivability, Kyoto University, Yoshida-Nakaadachi 1, Sakyo-ku, Kyoto 606-8306, Japan. Electronic address: ke.deng.57z@st.kyoto-u.ac.jp.
Takahashi K; Center for Social & Environmental Systems Research, National Institute for Environmental Studies, 16-2, Onogawa, Tsukuba, Ibaraki 305-8506, Japan.
Takakura J; Center for Social & Environmental Systems Research, National Institute for Environmental Studies, 16-2, Onogawa, Tsukuba, Ibaraki 305-8506, Japan.
Takara K; Disaster Prevention Research Institute (DPRI), Kyoto University, Uji, Kyoto 611-0011, Japan.
Kamranzad B; Department of Civil and Environmental Engineering, University of Strathclyde, Glasgow G11XJ, United Kingdom.

Sci Total Environ ; 873: 162283, 2023 May 15.

Article em En | MEDLINE | ID: mdl-36801340

Assuntos

Ambulâncias; Temperatura Alta; Japão; Temperatura; Tempo (Meteorologia)

Palavras-chave

Climate change; Emergency ambulance calls; Extreme Gradient Boosting; Heat-related impacts; Shared Socioeconomic Pathways (SSP)

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Ambulâncias / Temperatura Alta Tipo de estudo: Prognostic_studies / Risk_factors_studies País/Região como assunto: Asia Idioma: En Revista: Sci Total Environ Ano de publicação: 2023 Tipo de documento: Article

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