Mayo Clinic Develops AI System for Surgical Site Infection Detection

According to a July 7 press release, Mayo Clinic researchers have developed an artificial intelligence (AI) system that can accurately detect surgical site infections (SSIs) from patient-submitted wound photos, potentially transforming postoperative care. Published in the Annals of Surgery, the study highlights a two-stage AI model trained on over 20,000 images from 6,000+ patients across nine Mayo Clinic hospitals. The system achieved 94% accuracy in identifying surgical incisions and showed strong performance (81% AUC) in detecting infections.

The AI tool aims to speed up diagnosis, reduce delays, and improve care—particularly valuable for outpatient and rural settings. Researchers emphasize its potential to serve as a frontline screening tool and reduce clinician workload. While further validation is ongoing, the team sees this innovation as a step toward reshaping surgical follow-up with AI-assisted monitoring.