Development and Validation of a Personalized Model With Transfer Learning for Acute Kidney Injury Risk Estimation Using Electronic Health Records

IMPORTANCE: Acute kidney injury (AKI) is a heterogeneous syndrome prevalent among hospitalized patients. Personalized risk estimation and risk factor identification may allow effective intervention and improved outcomes. OBJECTIVE: To develop and validate personalized AKI risk estimation models usin...

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Detalles Bibliográficos
Autores principales: Liu, Kang, Zhang, Xiangzhou, Chen, Weiqi, Yu, Alan S. L., Kellum, John A., Matheny, Michael E., Simpson, Steven Q., Hu, Yong, Liu, Mei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Medical Association 2022
Materias:
Original Investigation
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9250052/
https://www.ncbi.nlm.nih.gov/pubmed/35796212
http://dx.doi.org/10.1001/jamanetworkopen.2022.19776

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9250052/
https://www.ncbi.nlm.nih.gov/pubmed/35796212
http://dx.doi.org/10.1001/jamanetworkopen.2022.19776

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