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.

“We hope these results will help test the effectiveness of new therapies for this form of MS and reduce the suffering patients experience,” said lead author of the study published in JAMA Neurology.

A recent fMRI-based study found that learning via electronic devices such as smartphones or tablets can inhibit the brain’s ability to understand scientific texts, according to a recent study published by Scientific Reports.

A commonly prescribed drug used to treat attention-deficit/hyperactivity disorder (ADHD) disproportionately affects the development of children’s brains compared to adults with ADHD, according to a new study published in Radiology.

GE Healthcare and Fujitsu Australia have announced a new collaboration focused on diagnosing and monitoring brain aneurysms using AI.

Researchers have developed a new machine learning system that can help pathologists make more accurate breast cancer diagnoses, sharing their findings in JAMA Network Open.

RBJ sought out a representative sampling of radiologists who are not just talking about AI but already using it to beneficial effect. Here are five highlights from what we found.