A team of Mayo Clinic researchers has developed an artificial intelligence (AI) system that can detect surgical site infections (SSIs) with high accuracy from patient-submitted postoperative wound photos, potentially transforming how postoperative care is delivered.
Published in the Annals of Surgery, the study introduces an AI-based pipeline the researchers created that can automatically identify surgical incisions, assess image quality and flag signs of infection in photos submitted by patients through online portals. The system was trained on over 20,000 images from more than 6,000 patients across nine Mayo Clinic hospitals.
“We were motivated by the increasing need for outpatient monitoring of surgical incisions in a timely manner,” says Cornelius Thiels, D.O., a hepatobiliary and pancreatic surgical oncologist at Mayo Clinic and co-senior author of the study. “This process, currently done by clinicians, is time-consuming and can delay care. Our AI model can help triage these images automatically, improving early detection and streamlining communication between patients and their care teams.”…