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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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| Опубликовано в: : | J Transl Med |
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| Главные авторы: | , , , , , , , , |
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
BioMed Central
2017
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| Предметы: | |
| Online-ссылка: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5679185/ https://ncbi.nlm.nih.gov/pubmed/29121946 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12967-017-1337-y |
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