Case Studies

Smart technologies are often touted as the answer to some of cardiology’s greatest challenges in patient care and practice. But where does hyperbole end and reality begin with artificial intelligence, machine learning and deep learning?

Developments in vastly scalable IT infrastructure will soon increase the rate at which machine learning systems gain the capacity to transform the field of medical imaging across clinical, operational and business domains. Moreover, if the pace seems to be picking up, that’s because data management on a massive scale has advanced exponentially over just the past several years. 

A new project is seeking to make MRI scans up to 10 times faster by capturing less data. NYU’s Center for Advanced Imaging Innovation and Research (CAI2R) is working with the Facebook Artificial Intelligence Research group to “train artificial neural networks to recognize the underlying structure of the images to fill in views omitted from the accelerated scan.”

Machine learning is one of the hottest topics in radiology and all of healthcare, but reading the latest and greatest ML research can be difficult, even for experienced medical professionals. A new analysis written by a team at Northern Ireland’s Belfast City Hospital and published in the American Journal of Roentgenology was written with that very problem in mind.

A compilation of the latest news in AI and machine learning

As an integrated health-delivery network comprising 13 hospital campuses, two research centers and a health plan with more than half a million subscribers sitting atop the biggest biobank with whole exome (DNA) sequence data in existence, Pennsylvania’s Geisinger Health System is one of the best-positioned institutions in the U.S. to explore the possibilities and initial successes of AI in healthcare. The institution is bringing complex algorithmic concepts to everyday patient care and showing others the path forward.

Medical imaging is in a big battle with big data. There’s too much data in too many locations, and most often they are not well managed. Data are clearly imaging’s most abundant yet most underutilized strategic asset. 

If you’ve seen one data center, you’ve seen them all. That’s what Charles Rivers believed, at least.

Like every American academic healthcare institution, SUNY Downstate Medical Center in Brooklyn, N.Y., is a beehive of activity in three overlapping yet distinct areas of focus—patient care, physician education and medical research. 

Bill Lacy, vice president of medical informatics at FUJIFILM Medical Systems U.S.A., spoke with Radiology Business about AI’s impact on radiologist workflow and what the company has planned for HIMSS19.

A family from Pennsylvania’s Plain People community, which consists primarily of Amish and Mennonite families, recently took their child to Cardiology Care for Children (CCC), a small yet regionally renowned practice in Lancaster.

Fourteen years ago, radiologist Dean R. Ball, DO, founded a breast imaging practice to meet the needs of the underserved communities in and surrounding Youngstown, Ohio. Today, the practice Ball founded, Tiffany Breast Care Center, employs 16 mammography staffers, up from five in 2004. Although the practice has grown significantly, Ball is committed to reading the X-ray images for each of his patients—which is upwards of 15,000 annually.