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The RSNA’s Foundational AI Certificate Program is an on-demand, self-paced course intended to support radiologists in using artificial intelligence in radiology. It consists of six modules of case-based and hands-on curriculum featuring expert instructors.
Content Areas (Codes):
The following Content Areas will be printed on the certificate for this course:
Start Date: 7/15/2026
Learning Objectives:
By the conclusion of this Foundational Radiology AI Program, you will have information to understand the foundation of AI in radiology including history, ethics, data curation and annotation, and clinical implementation :
- Prepare radiologists, physicists, data scientists, and clinical researchers to safely evaluate, implement, use, and monitor performance of AI-based tools for medical imaging
- Provide coordinated and comprehensive AI education that prepare radiologists to evaluate and use AI algorithms for clinical practice
- Provide participants with an understanding of AI algorithm development
- Provide participants the ability to safely evaluate, deploy, monitor, and use AI algorithms within their practice
Price:
Basic Member Rate: $725.00
Standard Member Rate: $575.00
Full Access Member Rate: $575.00
Member-in-training Rate: $425.00
Non-Member Rate: $725.00
Refund / Exchange Policy:
RSNA will not issue any refunds or exchanges for online only versions of educational products or activities purchased online. Please review the entire product or activity description prior to purchase.
RSNA Disclaimer:
The opinions or views expressed in this activity are those of the presenters and do not necessarily reflect the opinions, recommendations or endorsement of the RSNA. Participants should critically appraise the information presented and are encouraged to consult appropriate resources for information surrounding any product or device mentioned. Information presented, as well as publications, technologies, products and/or services discussed, are intended to inform the learner about the knowledge, techniques, and experiences of RSNA faculty who are willing to share such information with colleagues. The RSNA disclaims any and all liability for damages to any individual user for all claims which may result from the use of said information, publications, technologies, products and/or services, and events.