Mayo Clinic has developed an artificial intelligence tool that accurately detects surgical site infections (SSIs) from patient-submitted photos in electronic health records. This innovation could revolutionize postoperative care by providing timely outpatient monitoring, the health system said.
WHY IT MATTERS
The new Vision Transformer AI model, trained on more than 20,000 images from 6,060 adult patients across nine Mayo Clinic hospitals, first identifies whether an image contains a surgical incision and then analyzes it for signs of infection.
Mayo Clinic's study, published in the Annals of Surgery this month, noted that images included in the evaluation required eligible patients to send them through the patient portal within 30 days of their surgeries.
The impetus for the tool is the growing administrative workload caused by a rise in outpatient surgeries and the increased frequency with which patients submit electronic surgical incision images through the health system's portal.
"Early identification of [SSI] is essential for reducing postoperative morbidity,” the study authors said.
