Mayo Clinic AI Accurately Detects Infections in Postoperative Wound Photos
July 7, 2025
Mayo Clinic researchers created an AI model to analyze patient photos for surgical site infection detection with strong accuracy.
Key Details
- AI system developed by Mayo Clinic automates detection of surgical site infections using patient-submitted wound images.
- Model was trained on 20,000+ images from more than 6,000 patients across nine hospitals.
- Two-stage Vision Transformer model: incision detection (94% accuracy) and infection detection (81% AUC).
- Demonstrated performance consistency across diverse patient demographics, addressing bias concerns.
- Potential to accelerate infection detection, reducing delays in follow-up care and costs.
- Further prospective studies are planned for clinical validation.
Why It Matters
This AI-based system could streamline postoperative care by facilitating early infection identification, especially during virtual follow-ups, improving outcomes and clinician workflows. The tool highlights progress in applying imaging AI to routine, patient-generated health data.