Development of a personalized diagnostic model for kidney stone disease tailored to acute care by integrating large clinical, demographics and laboratory data: the diagnostic acute care algorithm - kidney stones (DACA-KS)
Abstract Background Kidney stone (KS) disease has high, increasing prevalence in the United States and poses a massive economic burden. Diagnostics algorithms of KS only use a few variables with a limited sensitivity and specificity. In this study, we tested a big data approach to infer and validate...
Main Authors: | , , , , , , , |
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Format: | Article |
Language: | English |
Published: |
BMC
2018-08-01
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Series: | BMC Medical Informatics and Decision Making |
Subjects: | |
Online Access: | http://link.springer.com/article/10.1186/s12911-018-0652-4 |