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

Ohmi WatanabeNorio NaritaMasahito KatsukiNaoya IshidaSiqi CaiHiroshi OtomoKenichi Yokota
Published in: Open access emergency medicine : OAEM (2021)
We could statistically make polynomial curves between the meteorological variables and the number of ambulance transport. We also preliminarily made DL-based prediction models. The DL-based prediction for daily ambulance transports would be used in the future, leading to solving the lack of medical resources in Japan.
Keyphrases
  • deep learning
  • air pollution
  • emergency medical
  • healthcare
  • electronic health record
  • current status
  • big data
  • artificial intelligence
  • machine learning
  • convolutional neural network