Explore the cutting-edge field of Explainable AI (XAI) in medical imaging through this 55-minute lecture by Dr. Nicolas Karakatsanis, Assistant Professor of Biomedical Engineering at Weill Cornell Medical College. Delve into a comprehensive taxonomy of XAI methods, focusing on post-hoc and ad-hoc techniques. Examine disease-specific XAI applications and the Co-12 categorization scheme. Gain valuable insights into the potential for clinical adoption of XAI in medical imaging, with detailed chapter breakdowns covering introduction, method classifications, and specific applications in the healthcare domain.
Explainable AI Techniques Towards Clinical Adoption in Medical Imaging
Molecular Imaging & Therapy via YouTube
Overview
Syllabus
Introduction
Taxonomy of XAI Methods
Post-hoc XAI Methods
Ad-hoc XAI Methods
Disease-specific XAI
Co-12 Categorization Scheme
Taught by
Molecular Imaging & Therapy
