Machine learning for patient risk stratification for acute respiratory distress syndrome
Published in PlosOne, 2019
Recommended citation: Zeiberg, Daniel, et al. "Machine learning for patient risk stratification for acute respiratory distress syndrome." PloS one 14.3 (2019): e0214465. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0214465
Existing prediction models for acute respiratory distress syndrome (ARDS) require manual chart abstraction and have only fair performance–limiting their suitability for driving clinical interventions. We sought to develop a machine learning approach for the prediction of ARDS that (a) leverages electronic health record (EHR) data, (b) is fully automated, and (c) can be applied at clinically relevant time points throughout a patient’s stay.