Improving precision of glomerular filtration rate estimating model by ensemble learning

BACKGROUND: Accurate assessment of kidney function is clinically important, but estimates of glomerular filtration rate (GFR) by regression are imprecise. METHODS: We hypothesized that ensemble learning could improve precision. A total of 1419 participants were enrolled, with 1002 in the development...

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Detalles Bibliográficos
Autores principales: Liu, Xun, Li, Ningshan, Lv, Linsheng, Fu, Yongmei, Cheng, Cailian, Wang, Caixia, Ye, Yuqiu, Li, Shaomin, Lou, Tanqi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5679185/
https://www.ncbi.nlm.nih.gov/pubmed/29121946
http://dx.doi.org/10.1186/s12967-017-1337-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5679185/
https://www.ncbi.nlm.nih.gov/pubmed/29121946
http://dx.doi.org/10.1186/s12967-017-1337-y

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