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Opportunities for Machine Learning and Noninvasive Sensing to Impact Emergency Cardiovascular Care

Title: Opportunities for Machine Learning and Noninvasive Sensing to Impact Emergency Cardiovascular Care

Organizers: Omer T. Inan (Georgia Institute of Technology); Jin-Oh Hahn (University of Maryland); Jacob Kimball (Georgia Institute of Technology)

Overview: While wearable sensing for cardiopulmonary health is typically covered in standard sessions at BHI, there is a compelling need to bring the emergency care community together for a special session aimed at (1) elucidating some of recent scientific discoveries in the field; (2) familiarizing the community with new sensing technologies, materials, and analytics methodologies; and (3) understanding some of the emerging sensing modalities and signal processing/system analysis algorithms. We anticipate that bringing these speakers together to discuss the latest trends in their respective areas will lead to synergistic opportunities for collaboration, and will also result in productive and exciting conversations at BHI for future research opportunities.

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