Title: AI in Mayo Hospital Medicine: From Prediction Models to Copilots and Clinical Agents
Presenters: Shant Ayanian, MD; Ray Qian, MD; Alexander J Ryu, MD
Date: May 20, 2026
Learning Objectives:
Upon completion of this activity, participants should be able to:
     -Differentiate predictive ML, generative AI, and agentic AI using Mayo-relevant hospital medicine examples
     -Interpret clinical ML model output safely, including calibration, thresholds, drift, bias, and workflow integration
     -Identify appropriate and inappropriate uses of enterprise AI tools in clinical, administrative, education, and research work
     -Recognize key risks, including hallucination, automation bias, privacy leakage, inequitable performance, and unclear accountability
     -Propose AI use cases where clinicians, informaticists, and data scientists can collaborate at Mayo
Contact Hours: 1.0

ATTENDANCE / CREDIT
Text the session code (provided only at the session) to 507-200-3010 within 48 hours of the live presentation to record attendance. All learners are encouraged to text attendance regardless of credit needs. This number is only used for receiving text messages related to tracking attendance. Additional tasks to obtain credit may be required based on the specific activity requirements and will be announced accordingly. Swiping your badge will not provide credit; that process is only applicable to meet GME requirements for Residents & Fellows.

TRANSCRIPT
Any credit or attendance awarded from this session will appear on your Transcript.

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