Emergency Certificate curriculum
The RSNA Imaging AI Certificate Program offers a pathway of certificate courses, providing you with the ability to harness the AI knowledge critical to meeting the challenges in the medical imaging field.
The curriculum described on this page is for the program’s Emergency Imaging AI Certificate course.
The Emergency Certificate course equips you with the vital skills you need to navigate the growing demands of emergency radiology and it provides a practical, focused look at imaging AI for radiologists who handle urgent or emergent cases and work in environments requiring immediate triage. The Emergency Certificate curriculum is designed for radiology professionals who are leading the implementation of AI solutions in clinical, emergency settings.
Enroll today and learn how to evaluate AI models, implement more efficient workflows, keep up with rapid report turnaround times and improve patient outcomes!
Outcomes and learning objectives
Upon completion of the six-module curriculum, enrollees will earn the Emergency Certificate, recognizing their ability to support every phase of emergency imaging AI—from assessment, to use case evaluation, to implementation.
Emergency Certificate learning objectives
- Gain a comprehensive understanding of assessing AI models through clinical, technical, and business perspectives.
- Examine various AI applications using multiple use cases in emergency radiology.
- Identify critical factors for the successful implementation of emergency radiology AI models.
Each of the six, case-based modules allow you to learn at your own pace through a series of pre-recorded videos and a variety of hands-on activities that build on concepts established in the previous modules.
Modules will be released on a monthly basis beginning Jan. 17.
Module 1: Refresher of AI
In module one, you will review neural networks, data curation, annotation and bias, NLP, workflow considerations and post-deployment monitoring.