Artificial intelligence can enhance radiologists’ ability to detect pulmonary nodules on chest CT scans while simultaneously reducing chest CT scan interpretation times.

While AI and robotics won’t be replacing physicians any time soon, emerging applications surely will lift efficiency for human practitioners of the healing arts and sciences. 

Deep learning designed to read single photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) can improve the diagnosis of coronary artery disease—a killer of more than 370,000 people in the U.S. annually.

The report, put out by the Journal of the American College of Radiology, is a companion roadmap to part one which was published April 16 in Radiology.

Body mass index, systolic blood pressure and smoking behaviors mediate the effects of education on cardiovascular health, according to a recent study in The BMJ.

A team of researchers used MR spectroscopy to analyze the impact of traffic-related air pollution on childhood neurological development. Their results were published in Environmental Research.

Researchers at Wake Forest School of Medicine in Winston-Salem, North Carolina, believe they have taken an important first step in developing a brain-based test to diagnose autism, according to the results of an fMRI-based study published in Biological Psychology.

Facebook researchers are working to see how well and how quickly robots can teach themselves to walk, feel their way around tricky spaces and otherwise try new robot-y things through AI-driven trial and error.