A new report, with contributions from the National Institute of Biomedical Imaging and Bioengineering (NIBIB), part of the National Institutes of Health, provides a roadmap for translational research on artificial intelligence (AI) in medical imaging. The report, published in the May 28, 2019, Journal of the American College of Radiology, identifies research priorities that leverage big data, the cloud, and machine learning for augmenting clinicians’ image planning and use to make diagnoses or assess patients’ responses to therapy.
This report and a companion report published last month summarize conclusions from an August 2018 workshop co-organized by NIH, the Radiologic American College of Radiology (ACR), the Radiological Society of North America (RSNA), and The Academy for Radiology and Biomedical Imaging Research. The first report published April 16, 2019, maps a path forward for foundational research in AI and this second report focuses on translational research necessary to deliver AI to clinical practice.
“Radiology has transformed the practice of medicine in the past century, and AI has the potential to radically impact radiology in positive ways,” said Krishna Kandarpa, M.D., Ph.D., co-author of the report and director of research sciences and strategic directions at NIBIB. “This roadmap is a timely survey and analysis by experts at federal agencies and among our industry and professional societies that will help us take the best advantage of AI technologies as they impact the medical imaging field.”