This post was contributed by Bibb Allen Jr., MD, FACR, American College of Radiology Data Science Institute (ACR DSI) Chief Medical Officer.
This week, I had the honor of co-chairing the National Institute of Biomedical Imaging and Bioengineering (NIBIB)’s Workshop on Artificial Intelligence (AI) in Medical Imaging.
ACR DSI Chief Science Officer Keith J. Dreyer, DO, PhD, FACR and I led or took part in important sessions to clarify the needs in foundational and translational research for medical imaging machine learning.
We outlined the ACR DSI process particularly as it relates to AI implementation and stressed that:
- The AI market is dependent upon both the development of AI algorithms and integration with current digital solutions (PACS, reporting systems, etc.)
- DSI is working with industry and other professional organizations to create standardized AI use cases
- AI solutions that do not follow AI use case standards will be slow to integrate into clinical practices
Proceedings from the workshop, which the ACR DSI co-sponsored, will ultimately be published as a research roadmap for healthcare and scientific professionals.
ACR Advocacy in Action will have much more on this important workshop next week.
- Which AI implementation issues will have the greatest impact in the “last mile” before deploying AI clinical tools?
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