Machine learning can read cardiac MRI scans––fast

Machine learning can read cardiac MRIs with the same accuracy as a physician, with much higher speed, according to a recent study published in Circulation: Cardiovascular Imaging and reported by Cardiovascular Business.

A trained physician typically needs about 13 minutes to analyze heart function on a cardiac MRI, which are commonly used to inform a number of procedures, including the timing of cardiac surgery, the implantation of cardioverter-defibrillators and determining if a patient should continue or cease cardiotoxic chemotherapy.

The AI method for reading 600 cardiac MRIs, as measured by Charlotte Manisty, MD, PhD, and colleagues in the study, accuracy was unchanged, but speed was vastly improved. In fact, leveraging AI to read the scans could save 54 clinician-days annually at every health center in the U.K.

See the full story below:

Amy Baxter

Amy joined TriMed Media as a Senior Writer for HealthExec after covering home care for three years. When not writing about all things healthcare, she fulfills her lifelong dream of becoming a pirate by sailing in regattas and enjoying rum. Fun fact: she sailed 333 miles across Lake Michigan in the Chicago Yacht Club "Race to Mackinac."

Around the web

Compensation for heart specialists continues to climb. What does this say about cardiology as a whole? Could private equity's rising influence bring about change? We spoke to MedAxiom CEO Jerry Blackwell, MD, MBA, a veteran cardiologist himself, to learn more.

The American College of Cardiology has shared its perspective on new CMS payment policies, highlighting revenue concerns while providing key details for cardiologists and other cardiology professionals. 

As debate simmers over how best to regulate AI, experts continue to offer guidance on where to start, how to proceed and what to emphasize. A new resource models its recommendations on what its authors call the “SETO Loop.”