SUMMARY
Michael J. Taunton, M.D., is an orthopedic surgeon who studies the use of advanced artificial intelligence (AI) to improve care for musculoskeletal conditions.
Dr. Taunton is a co-investigator in the Orthopedic Surgery Artificial Intelligence Laboratory at Mayo Clinic. The lab explores how AI can help doctors diagnose, plan and manage treatments more accurately and efficiently.
Dr. Taunton's major areas of study in the lab include predictive modeling to assess surgical risks, AI-powered image processing for enhanced surgical precision, and data analysis tools for better patient classification and outcomes. Dr. Taunton and his team conduct research in all subdisciplines of orthopedics, including hip and knee reconstruction, shoulder and elbow reconstruction, spine, pediatric orthopedics, sports medicine, trauma, musculoskeletal oncology, hand and wrist, and foot and ankle.
Focus areas
- Predictive patient risk models. Dr. Taunton develops algorithms to predict surgical risks and outcomes, which helps surgeons better customize treatments to individual needs.
- Automated image annotation and analysis. Enhancing the precision of medical imaging using AI helps identify critical features quickly and accurately, which is vital for both diagnosis and surgical planning.
- Synthetic image generation. Generating digital simulations of surgical scenarios helps surgeons prepare and execute complex procedures with greater confidence and success.
- Data-driven patient phenotyping. Using machine learning to parse large datasets helps improve the classification of conditions and tailoring of care protocols.
- AI in postoperative monitoring. Applying AI to monitor recovery after surgery helps optimize follow-up care and enable earlier detection of potential complications.
Significance to patient care
Dr. Taunton's research is revolutionizing care by integrating AI into the clinical workflow. This integration greatly improves the accuracy of diagnosis and the effectiveness of treatment. AI-driven tools developed in the lab reduce the time needed for medical imaging analysis, improve the customization of surgical plans, and enable better monitoring of recovery. These advancements lead to safer surgical procedures, quicker recoveries and better overall health outcomes for people with orthopedic conditions.