Seven Takeaways from a New Guidance on AI Implementation in Radiology

Recognizing the potential benefits and daunting challenges of incorporating artificial intelligence (AI) models into radiology workflows, researchers have published a guidance that examines four key questions on the process for evaluating and implementing AI-enabled modalities into practice. In the recently published Radiology article, the authors discuss the makeup of an AI governance and management structure, pertinent factors for assessing AI-powered imaging modalities, parameters for implementation into practice as well as monitoring of AI tools for effectiveness. Here are seven key takeaways from the guidance. Not only are radiologists represented in organizational AI governance structures, the study authors also pointed out that radiology groups are leading the implementation of AI imaging at many health-care institutions. However, the involvement of end users of the AI software is particularly critical, according to the article authors.