AI and other emerging technologies are soon to turn traditional nurses into information integrators. But nurses should be assured that technology will support their profession, not replace it.

Grey matter atrophy impacts localized brain regions that are functionally connected in patients with multiple sclerosis (MS), according to a new study published in Clinical Radiology. The results may serve as a framework for developing imaging biomarkers.

A team of researchers backed by a division within the National Institutes of Health (NIH) has created a novel MRI technique that can image a thinking brain 60-times faster than traditional methods.

The United States published more AI-based radiology studies than any other country across the globe, according to a new analysis released Aug. 15 in the American Journal of Roentgenology.

The United States is a global leader in publishing AI-based radiology research, according to new findings published in the American Journal of Roentgenology.

A machine learning method trained on synthetic breast ultrasound elastography images accurately classified tumors when applied to real-world images, according to a new study published in the August issue of Computer Methods in Applied Mechanics and Engineering.

Machine learning models can be trained to learn from how radiologists make decisions when interpreting screening mammograms, according to a new study published in the Journal of Digital Imaging. Such research may have a significant impact if used to train specialists.

A season of football can significantly damage a player’s brain, even if they did not experience a concussion. The results bolster evidence that suggests even repeated hits to the head can cause impactful brain damage.