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.

Deep learning algorithms can manage thyroid nodules on ultrasound (US) images at a level comparable to expert radiologists, according to new research published in 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.

Researchers have used AI to gain additional insight from the brain MRI scans of multiple sclerosis (MS) patients, sharing their findings in Nature Digital Medicine.

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