The REF-AI Workshop on Responsible, Explainable, and Fair AI for Medical Imaging Informatics addresses an urgent need within the broader healthcare settings, particularly in medical imaging informatics. With the rapid advancements in AI-driven solutions for medical imaging, there is a pressing need to build, train, and validate these AI models in ways that are transparent, fair, and aligned with ethical standards. The significance of this workshop lies in its focus on AI applications that can support equitable patient care, meet regulatory standards, enhance trustworthy AI, and enhance clinical decision-making without introducing unintended biases. As healthcare providers, regulatory parties, clinicians, and patients call for more accountable AI practices, the REF-AI workshop will offer a timely platform to bridge current research and real-world applications, addressing challenges and opportunities for better AI-powered healthcare.

Submission Guidelines

All papers must be original and not simultaneously submitted to another journal or conference. The following paper categories are welcome:

•  full-paper (4-6 pages), short, and position-paper (2-4 pages) submissions from both academia and industry.

Committees

Workshop Organizers

• Dr. Soheyla Amirian, Seidenberg School of Computer Science and Information Systems, Pace University, USA
• Dr. Prashnna K. Gyawali, Lane Department of Computer Science and Electrical Engineering, West Virginia University, USA
• Dr. Johannes F. Plate, Department of Orthopaedic Surgery, University of Pittsburgh, USA
• Dr. Ahmad P. Tafti, Department of Health Information Management, School of Health and Rehabilitation Sciences, University of Pittsburgh, USA
• Hands-on-practice session: Nick Littlefield, Intelligent Systems Program, University of Pittsburgh, USA

Contact

All questions about submissions should be emailed to samirian@pace.edu; tafti.ahmad@pitt.edu, or prashnna.gyawali@mail.wvu.edu