Deep learning for Etiology of Chronic Kidney Disease in Taiwan

Sheng-Min Chiu, Feng-Jung Yang, Yi-Chung Chen, Chiang Lee
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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.
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台湾慢性肾脏疾病病因学之深度学习研究
研究人员对空气污染和慢性肾病之间的联系进行了广泛的研究。然而,两者之间的关系尚不清楚。建立这种联系变得复杂,部分原因是各地的空气质量差异很大。因此,本研究设计了一个深度学习模型,分析空气污染数据与慢性肾脏疾病之间的关系。实验采用台湾地区医院的真实数据。此外,我们也验证了这些方法可以帮助台湾医院团队更好地了解空气污染与慢性肾脏疾病的关系,并提出后续有效的医疗改善计划。
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