Characterizing the temporal changes in association between modifiable risk factors and acute kidney injury with multi-view analysis.

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作者： Kang,Liu ^[1] ; Borong,Yuan ^[2] ; Xiangzhou,Zhang ^[3] ; Weiqi,Chen ^[3] ; Lav P,Patel ^[4] ; Yong,Hu ^[5] ; Mei,Liu ^[6]

作者单位： Big Data Decision Institute, Jinan University, Guangzhou, Guangdong, China; School of management, Jinan University, Guangzhou, Guangdong, China. ^[1] Big Data Decision Institute, Jinan University, Guangzhou, Guangdong, China; College of information science and technology, Jinan University, Guangzhou, Guangdong, China. ^[2] Big Data Decision Institute, Jinan University, Guangzhou, Guangdong, China. ^[3] Division of Medical Informatics, Department of Internal Medicine, University of Kansas Medical Center, Kansas City, KS, USA. ^[4] Big Data Decision Institute, Jinan University, Guangzhou, Guangdong, China. Electronic address: yonghu@jnu.edu.cn. ^[5] Division of Medical Informatics, Department of Internal Medicine, University of Kansas Medical Center, Kansas City, KS, USA. Electronic address: meiliu@kumc.edu. ^[6]

关键词 Acute kidney injury Electronic health records Machine learning Multi-view analysis Prevention

主题词急性肾损伤(Acute Kidney Injury);算法(Algorithms);电子健康病历(Electronic Health Records);人类(Humans);回顾性研究(Retrospective Studies);危险因素(Risk Factors)

DOI 10.1016/j.ijmedinf.2022.104785

PMID 35504130

发布时间 2022-07-21

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