Predicting Severe Sepsis Using Text from the Electronic Health Record
Abstract
Models predict severe sepsis based solely on unstructured EHR text, outperforming structured data alone and showing advantages for this type of data in medical modeling.
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.
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