July 7, 2025- 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.
The AI system uses a two-stage model. First, it detects whether an image contains a surgical incision and then evaluates whether that incision shows signs of infection. The model, Vision Transformer, achieved a 94% accuracy in detecting incisions and an 81% area under the curve (AUC) in identifying infections.