Open AccessA Concept–Wide Association Study of Clinical Notes to Discover New Predictors of Kidney Failure
Author(s) -
Karandeep Singh,
Rebecca A. Betensky,
Adam Wright,
Gary C. Curhan,
David W. Bates,
Sushrut S. Waikar
Publication year - 2016
Publication title -
clinical journal of the american society of nephrology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.755
H-Index - 151
eISSN - 1555-905X
pISSN - 1555-9041
DOI - 10.2215/cjn.02420316
Subject(s) - medicine , hazard ratio , confidence interval , nephrology , kidney disease , proportional hazards model , intensive care medicine , disease
Identifying predictors of kidney disease progression is critical toward the development of strategies to prevent kidney failure. Clinical notes provide a unique opportunity for big data approaches to identify novel risk factors for disease.
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