Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
2637675 | American Journal of Infection Control | 2014 | 4 Pages |
Abstract
Text mining techniques to detect surgical site infections (SSI) in unstructured clinical notes were used to improve SSI detection. In conjuction with data from an integrated electronic medical record, all of the 22 SSIs detected by traditional hospital-based surveillance were found using text mining, along with an additional 37 SSIs not detected by traditional surveillance.
Keywords
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Authors
James D. Michelson, Jenna S. Pariseau, William C. Paganelli,