Description
Back to topThe integration of AI systems into clinical workflows promises to improve the quality and efficiency of care, yet realizing this potential requires solutions that are not only mathematically sound but also operationally viable, ethically feasible, and clinically acceptable. This workshop will focus on the design and deployment of decision-support tools that work alongside human clinicians, with particular attention to ensuring that algorithmic systems perform equitably across diverse populations and address the sources of bias that arise due to heterogeneity in AI deployment. Particular emphasis will be placed on human-in-the-loop and hybrid models of decision-making that account for the behavior, preferences, and judgment of the clinicians and patients involved, taking up questions of trust, complementarity, accountability, and governance in real-world systems. Thus, the workshop aims to advance human-centered machine learning designs that directly improve patient outcomes and to chart research directions for the responsible deployment of AI in healthcare.
Lightning Talks
This workshop will include lightning talks for early career researchers (including graduate students). In order to propose a lightning talk, you must first register for the workshop, and then submit a proposal using the form that will become available on this page after you register. The registration form should not be used to propose a lightning talk.
The deadline for proposing is Sunday February 13, 2028. If your proposal is accepted, you should plan to attend the event in-person.
Registration Fees
A non-refundable registration fee will be payable by credit card or debit card for any participants invited to attend this workshop in-person. In-person participants agree to pay the non-refundable fee by the deadline given by IMSI. Failure to pay the fee by the deadline may mean that the invitation to attend in-person is revoked.
Current fees:
- $25 for students
- $50 for non-students