Workshop

Responsible, Explainable, and Fair AI for Medical Imaging Informatics (REF-AI)

In conjunction with IEEE/ACM CHASE 2025, Manhattan, New York City, USA.

Overview:

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.

Call for Papers:

We invite researchers, practitioners, and experts in artificial intelligence (AI), healthcare, medical imaging, and related fields to submit papers to the REF-AI Workshop on Responsible, Explainable, and Fair AI for Medical Imaging Informatics. This workshop will be held in conjunction with the IEEE/ACM CHASE 2025 and will be focusing on the ethical, technical, and practical challenges of deploying AI solutions in medical imaging.

REF-AI Workshop Themes

This workshop is well-equipped with keynote talk, panel discussions, and hands-on-practice, aiming to advance the development of AI-driven solutions that are not only accurate and effective in clinical settings but also uphold principles of responsibility, transparency and explainability, and fairness. We welcome original research, case studies, and position papers on topics including, but not limited to:
  • Foundations of responsible, explainable, and fair AI (REF-AI) in medical image analysis
  • Fairness, interpretability, and transparency in medical image analysis algorithms
  • AI accountability and regulatory considerations in healthcare applications
  • Impact of REF-AI principles on clinical decision-making
  • Ethical implications and social impacts of AI in medical imaging informatics
  • Real-world applications and case studies in medical imaging informatics
  • Bias mitigation strategies in medical image segmentation, registration, and classification

Submission Guidelines

We welcome submissions from both academia and industry in the following formats:
  • Full Papers: Comprehensive research studies (8-10 pages, IEEE format)
  • Short Papers: Concise studies, case reports, or preliminary findings (4-6 pages, IEEE format)
  • Position Papers: Thought-provoking discussions or critiques (2-4 pages, IEEE format)
All papers should be formatted according to the IEEE guidelines and submitted through the official con- ference submission portal. Each paper will undergo a peer-review process, and accepted papers will be included in the CHASE workshop proceedings.

Important Dates of REF-AI Workshop:

  • Workshop Paper Submission Deadline: February 1, 2025.
  • Workshop Paper Acceptance: March 3, 2025.
  • Workshop Camera-Ready Paper: March 10, 2025.

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