Deep learning techniques can be used to detect catheters and tubes in pediatric x-rays, according to a new study published in the Journal of Digital Imaging. These findings could lead to advancements that prioritize x-rays with poorly placed catheters, bringing them to a specialist’s immediate attention.
A detailed roadmap outlining research priorities for artificial intelligence (AI) in radiology was published April 16 in Radiology, and the organizations involved have announced that a second report is due later this year.
Using computer-aided detection (CAD) software powered by artificial intelligence leads to fewer false-positive mammograms, according to new findings published by the Journal of Digital Imaging. Significant cost savings could also be realized by making such a switch.
Artificial intelligence and machine learning technologies could fundamentally change healthcare forever, both for providers and their patients. A new analysis published in the New England Journal of Medicine examined that potential shift in great detail.
The American College of Radiology (ACR) Data Science Institute (DSI) has launched ACR AI-LAB, a new software platform that helps radiologists create, validate and use artificial intelligence to treat patients.