Prediction of the number of asthma patients using environmental factors based on deep learning algorithms.

Journal: Respiratory research
PMID: 38041105

Abstract

BACKGROUND: Air pollution, weather, pollen, and influenza are typical aggravating factors for asthma. Previous studies have identified risk factors using regression-based and ensemble models. However, studies that consider complex relationships and interactions among these factors have yet to be conducted. Although deep learning algorithms can address this problem, further research on modeling and interpreting the results is warranted.

Authors

  • Hyemin Hwang
    Environmental Engineering Department, Ajou University, Suwon, 16499, Korea.
  • Jae-Hyuk Jang
    Department of Allergy and Clinical Immunology, Ajou University School of Medicine, Suwon, 16499, Korea.
  • Eunyoung Lee
    Department of Neurology, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA.
  • Hae-Sim Park
    Department of Allergy and Clinical Immunology, Ajou University School of Medicine, Suwon, 16499, Korea.
  • Jae Young Lee
    Department of Radiology and the Institute of Radiation Medicine, Seoul National University Hospital, Seoul, Republic of Korea. leejy4u@gmail.com.

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