Title:   Digital Medicine and the Curse of Dimensionality:    Developing Clinical AI Models that Work Is Hard   

Learning Objectives:    Upon conclusion of this activity, participants should be able to:

• Identify the limitations associated with clinical AI models developed using a very large number of clinical variables
• Assess the generalizability of published clinical AI models (generalizability = the likelihood that the models will work when deployed in the real world)
• Identify approaches for improving the generalizability of clinical AI models 

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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