Effectiveness of cascading time series models based on meteorological factors in improving health risk prediction

Meteorological factors, which are periodic and regular in a long run, have an unignorable impact on human health. Accurate health risk prediction based on meteorological factors is essential for optimal allocation of resource in healthcare units. However, due to the non-stationary and non-linear nat...

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Veröffentlicht in:	Environmental science and pollution research international 2022-02, Vol.29 (7), p.9944-9956
Hauptverfasser:	Jia, Shuopeng, She, Weibin, Pi, Zhipeng, Niu, Buying, Zhang, Jinhua, Lin, Xihan, Xu, Mingjun, She, Weiya, Liao, Jun
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Aquatic Pollution Atmospheric models Atmospheric Protection/Air Quality Control/Air Pollution Climate prediction Deep learning Dose-response effects Earth and Environmental Science Ecotoxicology Electronic health records Electronic medical records Environment Environmental Chemistry Environmental Health Environmental science Health care Health risk assessment Health risks Health Status Humans Long short-term memory Machine learning Meteorological Concepts Meteorological data Noise prediction Outdoor air quality Patients Prediction models Research Article Resource allocation Respiratory tract Respiratory tract diseases Respiratory Tract Infections - epidemiology Time Factors Time series Waste Water Technology Water Management Water Pollution Control Windows (intervals)
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