Researchers from Massachusetts General Hospital (MGH) and Harvard Medical School developed a deep learning (DL) model that measures breast density “at the level of an experienced mammographer.” Results of the study were published in Radiology.

Decision support (DS) systems based on artificial intelligence (AI) can improve the diagnostic performance of radiologists, but what’s the best way to integrate those DS systems into a reader’s workflow? Researchers tested two different reading methodologies, sharing their findings in the Journal of Digital Imaging.

New survey results published in the American Journal of Roentgenology suggest there is gender bias within intervention radiology (IR), and it affects women throughout their entire career.

Patients turning to YouTube for high-quality information about transrectal ultrasound (TRUS)-guided biopsies of the prostate should look elsewhere, according to new research published in Clinical Radiology.

William Hsu, PhD, an associate professor of radiological sciences at UCLA, is the first deputy editor of RSNA’s new online journal, Radiology: Artificial Intelligence.

The Massachusetts Institute of Technology (MIT) announced a $1 billion commitment to “address the global opportunities and challenges presented by the prevalence of computing and the rise of artificial intelligence (AI).”

Many women—including insured women with full-time jobs—face significant out-of-pocket costs after being diagnosed with breast cancer. It leads to many hard-to-answer questions: What should they do? Who can they turn to for help?

A little more than a year ago, I left my full partnership position at a successful radiology practice for a teleradiology job with vRad, a MEDNAX company. I was a bit nervous making such a life-changing decision, but I knew I needed a change. Partnership had been a life goal since med school, but now I had different priorities. I had kids, new interests. Making the move allowed me to focus more on me and my family while still doing the work that I love.