DAY 1, May 22, 2023 (10:00 am to 2:00 pm EDT) 

Welcome and Opening Comments

Keyvan Farahani, PhD, Center for Biomedical Informatics and Information Technology, National Cancer Institute, National Institutes of Health

Session 1: Report of the MIDI Task Group

Report of the Medical Image De-Identification (MIDI) Task Group - Best Practices and Recommendations

Session Chair: David Clunie, MBBS, PixelMed, Inc.

In this session, David Clunie, chair of the MIDI Task Group, will summarize the best practices and recommendations included in the task group's report, recently available in pre-print, followed by a question and answer period.

Session 2: Tools for Conventional Approaches to De-Identification

Session Chair: Fred Prior, PhD, University of Arkansas for Medical Sciences

In this session, speakers will share methods currently in use for medical de-identification.

Session 3: International Approaches to De-Identification

Session chair: Bill Parker, MD, DABR, FRCPC, University of British Columbia

This session will focus on international approaches to de-identification.

Session 3: Industry Approaches to De-Identification

Session chair: Keyvan Farahani, PhD, Center for Biomedical Informatics and Information Technology, National Cancer Institute, National Institutes of Health

The priorities of and approaches by industry when it comes to protecting human identity in medical images can differ from those of governments. This session will examine those priorities and approaches with presentations by various industry groups.

Closing Remarks

David Clunie, MBBS, PixelMed, Inc.

DAY 2, May 23, 2023 (10:00 am to 2:00 pm EDT) 

Welcome and Recap

David Clunie, MBBS, PixelMed, Inc.

Session 4: Statistical Risk Analysis of Indirect Identifiers in an Image Context

Session chair: Mark Elliot, PhD, University of Manchester

In this session, researchers will discuss how to analyze the re-identification risk of indirect identifiers in medical images.

Session 5: De-Facing

Session chair: Ying Xiao

This session will focus on real-world evidence (RWE) data modeling, including issues associated with RWE data such as electronic health record coding and unbalanced data, towards the development of clinical trials.

Session 6: Cross-cutting discussion with session chairs

Session chair: Olivier Gevaert, Stanford University

Discussion of the approaches and challenges identified during the workshop and opportunities for the future.

Panelists:

Caroline Uhler, MIT and Broad Institute
Trey Ideker, UCSD
Dana Pe’er, Memorial Sloan Kettering
Ziad Obermeyer, UC Berkeley
Tianxi Cai, Harvard