Presenters:
Tufia Haddad, M.D.
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LEARNING OBJECTIVES
Upon completion of this activity, participants should be able to:

• Describe key barriers contributing to the translational gap between AI innovation and real-world clinical impact.
• Differentiate between AI as an algorithm, a model and clinical product.
• Apply a product-oriented framework to define high-value clinical problems appropriate for AI solutions.
• Identify system-level strategies to embed AI into clinical workflows to improve adoption and measurable patient outcomes.

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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