Summary
Currently, surgical site infection surveillance relies on labour-intensive manual chart review. Recently suggested solutions involve machine learning to identify surgical site infections directly from the medical record. Deep learning is a form of machine learning that has historically performed better than traditional methods, while being harder to interpret. This study proposed a deep learning model—an explainable long short-term memory network—for the identification of surgical site infection from the medical record.
The study found that the model had greater sensitivity when compared to traditional machine learning methods.
An explainable long short-term memory network for surgical site infection identification (13 April 2024)
https://www.surgjournal.com/article/S0039-6060(24)00142-9/abstract
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