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!

Individual pricing and enrollment

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. 

Hear from the course directors

Course directors Howard Chen, MD, MBA, and Nina Kottler, MD, MS, highlight the benefits and key takeaways of the Emergency Certificate course, empowering you to leverage AI in emergency imaging.

Course modules

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.

All six modules are available upon enrollment.

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​.

Module 2: How to Evaluate AI Models
In Module 2, you will learn business, technical and clinical evaluations including determining ROI and developing collaborative opportunities, workflow integration, use of IHE standards and model effectiveness. You will also learn about reviewing the market and where to find FDA-cleared and other agency-cleared information.
Module 2B: AI Implementation: Building Expertise and Influence (Hands-On)
In this hands-on module, you will run three experiments training an AI model, testing how to use AI for yourself. You will learn to incorporate standard practices and how to avoid key pitfalls when building your algorithms.
Module 3: Triage of Acute Emergent Findings
During this module, you will explore the use of CADt products in care coordination for radiologists and non-radiology clinicians. You will understand the value of AI products to various stakeholders in the imaging value chain at your institution. And, you will learn to evaluate available FDA-cleared AI algorithms for suitability to your practice.
Module 4: Ensuring Proper Follow-up of Critical and Non-Critical Findings
In Module 4, you will gain expertise with the different care coordination pathways and identify the role of AI-based automation in enhancing care coordination. You will learn about the significance of the radiologist’s role in care coordination and develop strategies that are important for optimal patient follow-up care.
Module 5: Improving Radiologist Efficiency (NLP/LLM/Gen AI Solutions)
In Module 5, you will understand the role of NLP and generative AI in radiology workflows. You will discover how AI technologies automate routine radiological tasks including pre- and post-reporting image analysis and data management. You will also explore ways AI can enhance report creation and accuracy.
Module 6: Implementation Considerations
In Module 6, you will learn to identify and access reliable resources for AI products that meet your specific needs. You will discover the principles of data drift monitoring tools, allowing you to discern their capabilities and limitations. You will also analyze consequences of overreliance on automated systems for human readers, identify parallels in other automation domains and explore strategies for integrating systems to mitigate biases effectively.

“ The hands-on component of the Emergency Certificate offers a great opportunity for participants to directly engage in training and evaluating a radiology AI model, all without requiring any coding experience. Speaking from personal experience, it was only after constructing my own algorithm that I fully came to understand AI. ”

— Luciano M. Prevedello, MD, MPH, Emergency Certificate course director

Contact us

Questions? Contact us at customerservice@rsna.org.