A maintenance hemodialysis mortality prediction model based on anomaly detection using longitudinal hemodialysis data-Reference-Cited by-同舟云学术

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A maintenance hemodialysis mortality prediction model based on anomaly detection using longitudinal hemodialysis data

Published:2021-11 Issue: Volume:123 Page:103930
ISSN:1532-0464
Container-title:Journal of Biomedical Informatics
language:en
Short-container-title:Journal of Biomedical Informatics

Author:

Wang Yu,Zhu Yilin,Lou Guofeng,Zhang Ping,Chen Jianghua,Li Jingsong

Funder

National Key Research and Development Program of China

Major Scientific Project of Zhejiang Laboratory

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Health Informatics,Computer Science Applications

Reference49 articles.

1. Changes in the US burden of chronic kidney disease from 2002 to 2016: An analysis of the global burden of disease study;Bowe;JAMA Netw. Open.,2018

2. Annual Data Report: Epidemiology of Kidney Disease in the United States;Saran;Am. J. Kidney Dis.,2018

3. The European Renal Association-European Dialysis and Transplant Association (ERA-EDTA) Registry Annual Report 2016: a summary;Kramer;Clin. Kidney J.,2019

4. Early mortality in patients starting dialysis appears to go unregistered;Foley;Kidney Int.,2014

5. Predictors of early mortality among incident US hemodialysis patients in the Dialysis Outcomes and Practice Patterns Study (DOPPS);Bradbury;Clin. J. Am. Soc. Nephrol.,2007

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2. Specific patterns and potential risk factors to predict 3-year risk of death among non-cancer patients with advanced chronic kidney disease by machine learning;Medicine;2024-02-16

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4. Assessment of Prediction Tasks and Time Window Selection in Temporal Modeling of Electronic Health Record Data: a Systematic Review;Journal of Healthcare Informatics Research;2023-08-14

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