Monitoring and Evaluating AI: Challenges and Practical Implications
Virtual 2020 SIIM-ACR Data Science Summit
Access recordings of all 6 sessions from the Virtual 2020 SIIM-ACR Data Science Summit, held on June 23, and earn up to 5.0 CME.
Whether you are a developer looking for insights from radiology leaders, or a radiologist with an informatics background seeking best practices, the Summit can help you understand best practices to evaluate AI models and provide strategies to overcome these potential barriers to AI adoption.
Course Overview:
- 5 hours of focused content
- 6 sessions of brief keynote presentations
- In depth panel discussions
Course Objectives:
Upon completion of the Summit, the participant will be able to:
- Identify phases of the AI lifecycle.
- Explain hurdles and steps to regulatory clearance.
- Define evaluations of AI and common issues including bias, brittleness, and fairness.
- Cite the tools and resources available to aid in the review and evaluation of AI models.
- Explain the steps of algorithm assessment and validation.
- Outline strategies for evaluating performance and monitoring AI algorithms.
The 2020 summit was held in conjunction with the virtual SIIM Annual Meeting.