Performance improvement of machine learning techniques predicting the association of exacerbation of peak expiratory flow ratio with short term exposure level to indoor air quality using adult asthmatics clustered data.

MLA

Bae, Wan D., et al. “Performance Improvement of Machine Learning Techniques Predicting the Association of Exacerbation of Peak Expiratory Flow Ratio with Short Term Exposure Level to Indoor Air Quality Using Adult Asthmatics Clustered Data.” PloS One, vol. 16, no. 1, Jan. 2021, p. e0244233. EBSCOhost, https://doi.org/10.1371/journal.pone.0244233.

APA

Bae, W. D., Kim, S., Park, C.-S., Alkobaisi, S., Lee, J., Seo, W., Park, J. S., Park, S., Lee, S., & Lee, J. W. (2021). Performance improvement of machine learning techniques predicting the association of exacerbation of peak expiratory flow ratio with short term exposure level to indoor air quality using adult asthmatics clustered data. PloS One, 16(1), e0244233. https://doi.org/10.1371/journal.pone.0244233

Chicago

Bae, Wan D, Sungroul Kim, Choon-Sik Park, Shayma Alkobaisi, Jongwon Lee, Wonseok Seo, Jong Sook Park, Sujung Park, Sangwoon Lee, and Jong Wook Lee. 2021. “Performance Improvement of Machine Learning Techniques Predicting the Association of Exacerbation of Peak Expiratory Flow Ratio with Short Term Exposure Level to Indoor Air Quality Using Adult Asthmatics Clustered Data.” PloS One 16 (1): e0244233. doi:10.1371/journal.pone.0244233.