Advancing AI algorithms into clinical practice: How can radiology lead the way?

Thought leaders within radiology largely agree that the specialty is in a unique position to help lead the implementation of artificial intelligence (AI) into clinical practice. But how, exactly, does that happen?

Despite low prevalence in the demographic, women younger than 40 years old should still undergo triple assessment for breast cancer—especially if they present with a symptomatic lump or have extensive family history of the disease, a team of U.K. researchers reported in Clinical Radiology this month.

Putting together a radiology elective that takes post-grads overseas for global outreach is a complex process, but it’s well worth the skills gained in confronting unfamiliar medical situations and learning to practice in resource-limited environments, according to a team of radiologists from across the country.

Radiology residents and medical students alike are driven more by fulfilling careers, work-life balance and interest in their specialty than financial aspirations or the job market itself, according to a Journal of the American College of Radiology-published study, suggesting trainees select a medical path based more on social and intrinsic motivations and less on external successes.

The American College of Radiology Foundation (ACRF) announced Monday, May 7, it is working with Rotary International and Imaging the World to help patients in need in Uganda.

It’s no secret that researchers often use MRI equipment in creative ways. That trend has been continued by a group that turned to functional MRI (fMRI) to view the brains of crocodiles as they were exposed to various sounds.

A Covington, Georgia, practice is encouraging everyone to treat their loved ones to an unusual gift this Mother’s Day—a mammogram.

Massachusetts doctors are quick to refer patients for expensive imaging services like MRI and CAT scanning, the Boston Business Journal reported this week—and it cost the federal government an estimated $27 million in 2015.

With few exceptions, the most attention-demanding discussions about how and when artificial intelligence will transform radiology have been led by—and largely held within—the academic sector. That’s not surprising, given that teaching radiologists are the ones doing the research, blazing the trails and comparing the notes.