AIHH Grand Rounds (MSH) 2025

1. Describe recent advances in AI tools for clinical diagnostics and evaluate when they should be appropriately applied in patient care.
2. Identify common implementation challenges and develop an action plan for integrating AI-based risk prediction models into routine clinical workflows.
3. Explain to healthcare providers and assess their understanding of how AI can personalize treatment recommendations to improve outcomes for patients with chronic conditions.

It is the policy of the Icahn School of Medicine at Mount Sinai to ensure objectivity, balance, independence, transparency, and scientific rigor in all CME-provided educational activities. All faculty participating in the planning or implementation of a provided activity are expected to disclose to the audience any relevant financial relationships and to assist in resolving any conflict of interest that may arise from the relationship. Presenters must also make a meaningful disclosure to the audience of their discussions of unlabeled or unapproved drugs or devices. This information will be available as part of the course material.

Mitigation of Relevant Financial Relationships

It is the policy of the Icahn School of Medicine at Mount Sinai to ensure objectivity, balance, independence, transparency, and scientific rigor in all accredited CE educational activities. All individuals in control of content of an activity accredited by ISMMS are expected to disclose all their financial relationships with ineligible companies existing within the prior 24 months. All relevant financial relationships have been mitigated and disclosed to learners before the activity takes place.