Predicting Severe Sepsis Using Text from the Electronic Health Record

Abstract

Employing a machine learning approach we predict, up to 24 hours prior, a diagnosis of severe sepsis. Strongly predictive models are possible that use only text reports from the Electronic Health Record (EHR), and omit structured numerical data. Unstructured text alone gives slightly better performance than structured data alone, and the combination further improves performance. We also discuss advantages of using unstructured EHR text for modeling, as compared to structured EHR data.

Accepted at workshop on Machine Learning For Health at the conference on Neural Information Processing Systems, 2017. Near-final draft version

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