Improved Surgical Site Infection Identification using Explainable Long Short-term Memory Network

A long short-term memory network with an attention layer was proposed for surgical site infection identification, achieving higher sensitivity and area under the receiver operating characteristic curve compared to traditional models. The model’s top features included procedure codes and laboratory values, offering explainability. This innovative approach could enhance automated surveillance and replace manual chart review processes for improved infection control.