AI/ML Task Force

Overview

 

The role of the AI/ML Task Force will be to provide expertise to the DPA in the following ways:

 

  • The AI/ML TF will develop AI/ML initiatives to cement the DPA as the “go-to” resource for AI/ML in pathology, including regulatory insight, best practices, scholarly activity, vendor relationships, and ethics.
  • The AI/ML TF will provide website content oversight, including vetting blog submissions and AI/ML-related content. Given the external facing nature of the website, a member of the AI/ML committee should be designated to attend Website Committee meetings and ideally should be encouraged to become a member of the Website Committee and Blog Vetting group.
  • The AI/ML TF will be asked to review concept papers developed by the Education Committee that are relevant to AI/ML.
  • The AI/ML TF will contribute expertise to the Regulatory and Standards Task Force in initiatives pertaining to AI/ML.
  • The AI/ML TF will be available to assist with other DPA efforts including Pathology Visions planning and speaker recruitment, webinar recruitment, and educational initiatives such as DAPA and PathologyOutlines content.

The AI/ML Task Force's initial charge will be to expand the DPA’s footprint beyond whole-slide imaging into computational pathology.  In addition to the above support activities, this will include the following initiatives:

 

  • Lead efforts alongside the Education Committee to develop a white paper on the ethics of AI/ML in digital pathology
  • Add AI/ML content to the web site’s FAQ pages, which is currently lacking AI
  • Create an AI/ML section of the DPA web site. This may include:
    • Educational content that synthesizes information such as the PV2019 “AI 101” lecture into an easy-to-access web-based format
    • Begin an AI/ML tools repository, similar in concept to the WSI Repository, in which basic tools necessary for processing whole-slide images are made available to researchers (e.g. WSI anonymization, patch extraction, data augmentation)
  • Pursue fee-based educational opportunities (similar to API’s recent Introduction to R Workshop).
  • Interact with AI/ML and image management system vendors to encourage interoperability, perhaps with plans to pursue a Connectathon-style demonstration.

If you are interested in joining this Committee, please email the DPA staff, info@digitalpathologyassociation.org

 

Committee Members

 

Chair: Mark Zarella

 

  • Stanley Cohen, MD, Rutgers-Rutgers
  • Toby Cornish, MD, PhD, University of Colorado
  • Steven Hart, Mayo Clinic
  • Andrew Janowczyk, PhD, Case Western Reserve University
  • George Lee, PhD, Bristol-Myers Squibb
  • Richard Levenson, MD, UC Davis - Pathology
  • Hooman Rashidi, UC Davis - Pathology
  • Hamid Tizhoosh, PhD, Kimia Lab, University of Waterloo
  • Jeroen van der Laak, PhD, Radboud University Medical Center
  • Joe Yeh, MD, aetherAI
  • Mark Zarella, PhD, Johns Hopkins University

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