Informatics e-Learning Hub

Lessons to Help You Bring AI to Practice
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Welcome to the Informatics e-Learning Hub!

AI tools are moving from rare to mainstream. To leverage the power of AI, we’re here to help you understand how it works and optimize its performance. Each focused topic area highlighted below offers a variety of on-demand videos developed by AI experts in medical imaging and the opportunity to learn, understand and incorporate best practices into your work.

Video Library

The Basics of AI

Start with the fundamentals. Learn key AI concepts through these five videos. You’ll hear how AI is developed and how AI tools can be applied to imaging data and improve radiology workflow. We’ll explore the areas of AI with the most tools available, look at bias and fairness in AI models, and explain what radiologists should look for in evaluating an AI algorithm.

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Bringing AI to Practice

Implementing AI can be challenging. Discover the steps to be successful. You’ll hear what to consider when incorporating AI into practice for the first time, including important processes to put into place. We’ll explain how to work with vendors, share issues with standardization, and dig into evaluating models for use in clinical practice.  Valuable ACR informatics tools and the ACR Imaging 3.0 initiative are included.

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Data Sharing

Access to data is crucial for the development of AI. Yet before safely sharing data, physicians face challenges, including defining who owns it, determining its value, and evaluating whether it should be shared. In this video series, we’ll explore the top considerations and look at how physicians can use data pooling and federated learning to create more generalizable AI models.

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Government Regulation and AI

As development of AI accelerates, it creates challenges for government regulation. You’ll hear a brief history of AI/ML regulation and learn the major pathways for software as a medical device to become commercially available. We’ll also cover proposed modifications to the regulatory framework for modifications to AI/ML and ACR initiatives to support the use of AI in medical imaging.

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