Artificial intelligence has made tremendous strides in medical imaging analysis over the past ten years. However, as these systems move closer to clin...
Kevin Haines, D.O., PGY-4 from University of Connecticut Health Center, shares an insightful recap of the 2024 Quality and Safety + Informatics Confer...
The ACR Quality and Safety + Informatics Conference provides a unique forum for quality and safety professionals to collaborate with informaticists, d...
This briefing is part of our series summarizing key research and articles to keep you up to speed on the latest in medical imaging AI.
The Open Imaging Data Model (OIDM) initiative seeks to define common data structures representing the data associated with clinical radiology exams. T...
While the ramifications of using AI on pediatric patients aren’t yet clear, the need for advocacy is.
ACR has been productive in developing the tools radiologists need to make progress with AI.
DICOM Supplement 224 will alleviate the roller-coaster rides of AI deployment by standardizing processing services and applications to help catalyze A...
Only with standardized, structured report data can machine learning be trained and trusted in quality patient care. The popularity of artificial intel...