1. Evaluate how machine learning and engineering methods can augment stroke and neurocritical care management 
  2. Summarize the basics of machine learning architecture for analysis 
  3. Explain current approaches in using signal processing and machine learning for neuroprognostication in cardiac arrest patients
  4. Describe current approaches and avenues in brain-machine-interface technology
  5. Develop an understanding of new computational-based research to guide diagnostic testing and interventions in stroke
Session date: 
05/11/2026 - 4:00pm to 5:00pm CDT
Location: 
Virtually
United States
See map: Google Maps
  • 1.00 AMA PRA Category 1 Credit™
  • 1.00 University of Wisconsin–Madison Continuing Education Hours
    • 1.00 Approved for AMA PRA Category 1 Credit™
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