Machine learning (ML) can help healthcare providers predict heart disease—including heart attacks—better than other popular risk models, according to new research published in Radiology.

As AI technologies continue to evolve, they may be able to make a significant impact on patient care by reducing the amount of time physicians spend sorting through paperwork and documentation.

“In a scenario where double reading at screening mammography is not available…we believe that the use of this model as a second reader could be beneficial,” wrote researchers in a new study published by Radiology.

Researchers have developed an algorithm that predicts breast malignancy using a patient's imaging results and detailed health records, sharing their findings in Radiology.

Canon Medical Systems USA announced Tuesday, July 18, that its new deep convolutional neural network (DCNN) image reconstruction solution for CT scans has received FDA approval.

AI marketplaces could have a significant impact on the future of radiology, according to a new analysis published by the Harvard Business Review.

Zebra Medical Vision announced Monday, June 17, that its AI solution for intracranial hemorrhage (ICH) alerts has gained FDA approval.

You can find just about anything in an app store. Soon, that may include artificial intelligence applications for radiologists, as a recent Harvard Business Review article suggested.