There has been an exponential increase in the number of publications and work pertaining
to applications of artificial intelligence (AI) and machine learning (ML) in medicine and in …

The 2018 AUR Academic Radiology and Industry Leaders Roundtable “Artificial Intelligence
(AI) in Radiology” discussion gives a high-level perspective of how AI is shaping the field of …

In the ubiquitous media coverage of artificial intelligence (AI) and machine learning,
radiology has emerged as the poster child for professions that will potentially be rendered …

The American College of Radiology (ACR)—a professional association representing nearly
40,000 diagnostic radiologists, interventional radiologists, nuclear medicine physicians …

Over 70% of FDA approved artificial intelligence (AI) tools are centered within radiology [1].
In 2008 one AI enabled device application was approved by the FDA for clinical use …

Radiology is often identified as a field well-suited for AI integration due to its intimate
relationship with informatics and reliance on digital imaging, but applications of medical AI …

Conclusions The application of AI and ML in clinical practice requires a more rigorous
approach than is currently used. Scalable, efficient collection and the use of curated, labeled …

Advances in machine learning in medical imaging are occurring at a rapid pace in research
laboratories both at academic institutions and in industry. Important artificial intelligence (AI) …

Despite the surge in artificial intelligence (AI) development for health care applications,
particularly for medical imaging applications, there has been limited adoption of such AI …

Bibb Allen, MD, FACR, CMO of the ACR's Data Science Institute (DSI), notes," AI-lite" is
already being used in radiology in a number of ways, such as computer-aided detection for …