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.
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