@inproceedings{1e199e75acc84da9a3cbc85100a7abb1,
title = "Deep learning for Etiology of Chronic Kidney Disease in Taiwan",
abstract = "The link between air pollution and chronic kidney disease has been broadly examined by researchers. However, the relationship between the two remains unclear. Establishing this link has been complicated in part by the fact that air quality varies considerably from place to place. Therefore, this study designed a deep learning model that analyzed the relationship between air pollution data and chronic kidney disease. The experiments utilized real hospital data in Taiwan. Furthermore, we verified that the methods could help hospital teams in Taiwan better understand the association of air pollution and chronic kidney disease and also proposed subsequent and effective medical improvement plans. ",
author = "Chiu, {Sheng Min} and Yang, {Feng Jung} and Chen, {Yi Chung} and Chiang Lee",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2nd IEEE Eurasia Conference on IOT, Communication and Engineering, ECICE 2020 ; Conference date: 23-10-2020 Through 25-10-2020",
year = "2020",
month = oct,
day = "23",
doi = "10.1109/ECICE50847.2020.9301997",
language = "English",
series = "2nd IEEE Eurasia Conference on IOT, Communication and Engineering 2020, ECICE 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "322--325",
editor = "Teen-Hang Meen",
booktitle = "2nd IEEE Eurasia Conference on IOT, Communication and Engineering 2020, ECICE 2020",
address = "United States",
}