| dc.description.abstract | In recent year, the influence on human beings of environmental factors increasing has
been a hot potato and there was a lot of research has shown the association between different
kinds of diseases and environmental factors, especially air pollutants and water quality.
Meanwhile, influence on individuals by environmental factors are not all the same, and the
diseases they get are different. Therefore, in this study, we want to implement an automatic
system to analyze the relationship between any disease on Longitudinal Health Insurance
Database (LHID) and environmental factors and construct deep learning-based models for
diseases prediction incorporating air status or water quality status. However, there is no
instantaneous value of water quality, so we focus on air pollutants on automatic analysis
system. The results show that even though there are some differences between the analytical
results from our system and the previous research, the similarities between them are in
majority. In diseases prediction, we show high performance on the overall forecast. Our
models considered medical information from LHID, incorporating air pollutants, location
information, and water quality. The accuracy among these four features is 89.49%, 89.59%,
89.59%, and 89.56% separately. In short, incorporating these environmental factors can
improve the accuracy of deep learning-based diseases prediction actually. | en_US |