Bringing radiology artificial intelligence (AI) technology to routine clinical practice will require four major priorities: structured use cases, data sharing methods, validation and monitoring tools, and new standards and data elements, according to a report published online May 28 in the Journal of the American College of Radiology. “An active AI ecosystem in which radiologists, their professional societies, researchers, developers, and government regulatory bodies can collaborate, contribute and promote AI in clinical practice will be key to translating foundational AI research to clinical practice,” wrote a team of authors of the American College of Radiology (ACR) Data Science Institute.
Following up on an initial medical imaging artificial intelligence roadmap published April 16 in Radiology, which covered the challenges, opportunities and priorities for foundational research in…
