System Maintenance Notice

Please note that maintenance work is scheduled between 4 AM and 5 AM - CET. During this time, you may experience reduced performance. Thanks for your patience.

Publications

Journal Article Research Support, Non-U.S. Gov't Epublish 3 citations

PubMed: 35681961 DOI: 10.3390/ijerph19116373

In the Seeking of Association between Air Pollutant and COVID-19 Confirmed Cases Using Deep Learning.

Int J Environ Res Public Health 19(11)

Authors: Yu-Tse Tsan, Endah Kristiani, Po-Yu Liu, Wei-Min Chu, Chao-Tung Yang

Affiliations

  • Department of Emergency Medicine, Taichung Veterans General Hospital, Taichung City 407204, Taiwan.
  • School of Medicine, Chung Shan Medical University, Taichung City 40201, Taiwan.
  • Division of Occupational Medicine, Department of Emergency Medicine, Taichung Veterans General Hospital, Taichung City 407204, Taiwan.
  • Department of Computer Science, Tunghai University, No. 1727, Sec. 4, Taiwan Boulevard, Taichung City 407224, Taiwan.
  • Department of Informatics, Krida Wacana Christian University, Jakarta 11470, Indonesia.
  • Division of Infection, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung City 407204, Taiwan.
  • Department of Family Medicine, Taichung Veterans General Hospital, Taichung City 407204, Taiwan.
  • School of Medicine, National Yang Ming Chiao Tung University, Taipei City 11221, Taiwan.
  • Department of Post-Baccalaureate Medicine, College of Medicine, National Chung Hsing University, Taichung City 40227, Taiwan.
  • Institute of Health Policy and Management, National Taiwan University, Taipei City 10617, Taiwan.
  • Research Center for Smart Sustainable Circular Economy, Tunghai University, No. 1727, Sec. 4, Taiwan Boulevard, Taichung City 407224, Taiwan.

Abstract

The COVID-19 pandemic raises awareness of how the fatal spreading of infectious disease impacts economic, political, and cultural sectors, which causes social implications. Across the world, strategies aimed at quickly recognizing risk factors have also helped shape public health guidelines and direct resources; however, they are challenging to analyze and predict since those events still happen. This paper intends to invesitgate the association between air pollutants and COVID-19 confirmed cases using Deep Learning. We used Delhi, India, for daily confirmed cases and air pollutant data for the dataset. We used LSTM deep learning for training the combination of COVID-19 Confirmed Case and AQI parameters over the four different lag times of 1, 3, 7, and 14 days. The finding indicates that CO is the most excellent model compared with the others, having on average, 13 RMSE values. This was followed by pressure at 15, PM at 20, NO at 20, and O at 22 error rates.

MeSH

Environmental Exposure, Environmental Pollutants, Covid-19, Deep Learning, Air Pollutants