Learning Data-Driven Patient Risk Stratification Models for Clostridium difficile

We take a data-driven approach to predicting which inpatients are most likely to test positive for pathogenic Clostridium difficile (C. difficile). Using EMR data from 69,568 admissions, we develop and validate a risk-stratification model, based on over 10,000 variables.

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