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Session Chair: Fred Prior, PhD, University of Arkansas for Medical Sciences
Speakers:
- Michael Rutherford, University of Arkansas for Medical Sciences
- Stephen Moore, Washington University School of Medicine in St. LouisSteve Moore
Break
Estimated at 11:55-12:05 p.m.
Session 3: International Approaches to De-Identification
This session will focus on requirements for de-identification outside of the United States.
Session chair: Will Parker, MD, DABR, FRCPC, University of British ColumbiaThis session will focus on requirements for de-identification outside of the United States.
Speakers:
- Speaker 1, TBD
- Speaker 2, TBD
Session 4: Industry Approaches to De-Identification
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Industry has a role to play in de-identification, developing tools that protect human identity in medical images. This session will feature presentations by industry groups that examine their approaches and offerings.
Session chair: Jürgen Klenk, PhD, Deloitte Consulting LLP
Speakers:
- Bob Lou, Google
- Lawrence (Tony) O’Sullivan, IBIS
- Rahul Krish, IBIS
- Dan Marcus, Flywheel
Closing Remarks
David Clunie, MBBS, PixelMed, Inc.
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Session 5: Pathology Whole Slide Image De-Identification
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In this session, researchers will discuss pathology whole slide image de-identification.
Session chair: Adam Taylor, PhD, Sage Bionetworks
Speakers:
- Tom Bisson
- David Gutman
Session 6: De-facing
Session chair: Ying Xiao, PhD, Hospital of the University of Pennsylvania
This session will focus on balancing the risks of removing potentially reconstructable facial information in head and neck cross-sectional images, also called de-facing, with the diminished utility of these images caused by restricted access to them.
Session chair: Ying Xiao, PhD, Hospital of the University of Pennsylvania
Speakers:
- Christopher Schwartz (Mayo Clinic)
- Douglas Greve (MGH/Harvard)
Break
Estimated at 11:50 a.m. - 12:00 p.m.
Session 7: The Role of AI in Image in De-Identification
Session chair: Judy Wawira Gichoya, MD, MS, Emory University
In this session, researchers discuss the utility and risk of using algorithms from machine learning (ML) and artificial intelligence (AI) to de-identify medical images.
Session chair: Judy Wawira Gichoya, MD, MS, Emory University
Speakers:
- George Shih
- Speaker 2, TBD
Session 8: Panel Discussion with Session Chairs
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