Prediction Model of Deep Learning for Ambulance Transports in Kesennuma City by Meteorological Data

PURPOSE: With the aging population in Japan, the prediction of ambulance transports is needed to save the limited medical resources. Some meteorological factors were risks of ambulance transports, but it is difficult to predict in a classically statistical way because Japan has 4 seasons. We tried t...

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Detalles Bibliográficos
Autores principales: Watanabe, Ohmi, Narita, Norio, Katsuki, Masahito, Ishida, Naoya, Cai, Siqi, Otomo, Hiroshi, Yokota, Kenichi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2021
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7850460/
https://www.ncbi.nlm.nih.gov/pubmed/33536798
http://dx.doi.org/10.2147/OAEM.S293551

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7850460/
https://www.ncbi.nlm.nih.gov/pubmed/33536798
http://dx.doi.org/10.2147/OAEM.S293551

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