Mayo Clinic College of Medicine and ScienceArtificial Intelligence in Healthcare (AIHC) Master’s Program & AIHC Education Committee MemberIntroduction to Deployment, Adoption & Maintenance of Artificial Intelligence Models/Algorithms

As the AI Validation & Stewardship Research Program Director at Mayo Clinic Health System, I lead the strategic development, research, and implementation of initiatives that ensure the safe, effective, and ethical deployment of AI technologies across clinical settings. My role involves integrating cutting-edge research with robust validation processes, implementing a risk-based evaluation approach, and fostering a quality management system that aligns with Mayo Clinic’s mission of putting patients first.A key aspect of my work is partnering with external innovators, research institutions, and technology companies to accelerate the translation of AI research into real-world clinical applications. I am committed to closing the AI translation gap, ensuring that innovative technologies move seamlessly from research and development to patient care. By harmonizing standards and collaborating with clinicians, data scientists, researchers, and regulatory bodies, I strive to advance responsible AI adoption that enhances patient care and outcomes while upholding the highest standards of clinical excellence, ethical practice, and research integrity in healthcare AI.

Our mission is to provide guidelines regarding an ever-evolving landscape of health AI tools to ensure high-quality care, increase credibility amongst users, and meet healthcare needs. I serve on the steering committee of CHAI and co-chair the CHAI Transparency Working Group. We are a community of academic health systems, organizations, and expert artificial intelligence (AI) and data science practitioners. Collectively, we work to harmonize standards and reporting for health AI and educate end-users on how to evaluate these technologies to drive their adoption.

The AMIA AI Evaluation Showcase Series aims to select and present the current use cases in the field and form a community to help build consensus around best practice. The community and the curated best practice examples are expected to strengthen the thought leadership position of the AMIA community in the industrial standard understanding and setting.