Artificial Intelligence at the Bedside: Can Large Language Models Enhance Diagnostic Reasoning?

Presenter: Dr. Bobak Seddighzadeh

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

• Analyze key clinical trials exploring the role of Large Language Models (LLMs) in diagnostic reasoning.
• Assess the strengths and limitations of LLMs in augmenting diagnostic reasoning.
• Develop strategies to effectively integrate LLMs into clinical decision support.

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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