AI Article Synopsis
- Text mining techniques were applied to identify surgical site infections (SSIs) from unstructured clinical notes, enhancing SSI detection.
- In conjunction with data from an integrated electronic medical record, this approach was able to identify all 22 SSIs found by traditional hospital surveillance.
- Additionally, it uncovered 37 more SSIs that traditional surveillance methods missed, demonstrating its effectiveness.
Article 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.
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| http://dx.doi.org/10.1016/j.ajic.2013.09.007 | DOI Listing |
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