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.

A robotic animal companion has been making the rounds at the University of Nebraska Medical Center, where a pediatric patient in intensive care is recovering from multiple organ transplants.

A new machine learning system created by UCLA researchers may help doctors classify breast cancers that are notoriously difficult to diagnose, according to an Aug. 9 study published in JAMA Network Open.

Machine learning models could help some patients with suspected pulmonary embolism (PE) avoid unnecessary CT imaging, according to new findings published in JAMA Network Open.

A neural network model can scour electronic medical record (EMR) data and determine if a patient has imaging-specific pulmonary embolism (PE)—a potential remedy for unnecessary CT imaging, reported authors of a multicenter study published in JAMA Network Open.

An attentive mechanical walking aid developed at Columbia University can help correct the gait of people who are unsure on their feet due to motor-skills challenges. In the process, the cane-like device may also reduce the risk of falls.

Machine learning algorithms can classify pathology reports and help providers track follow-up imaging recommendations, according to new findings published in Radiology: Artificial Intelligence.