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

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.

Methods

In this study, from 2015 to 2019, information about air pollutants, weather conditions, pollen, and influenza were utilized to predict the number of emergency room patients and outpatients with asthma using recurrent neural network, long short-term memory (LSTM), and gated recurrent unit models. The relative importance of the environmen

SUBMITTER: Hwang H 

PROVIDER: S-EPMC10693131 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature