First-of-its-kind trial shows AI beat humans at analyzing heart scans

AI beat humans
AI beat humans

An AI trained to assess heart scans outperformed human technicians, both in terms of accuracy and efficiency, in a first-of-its-kind trial.

“There’s a lot of hype and a lot of excitement around AI, but really this is the first piece of very concrete evidence that this is ready for clinical use,” said trial leader David Ouyang, a cardiologist at Cedars-Sinai Medical Center.

The challenge: Measuring the percentage of available blood that leaves the heart with each pump — known as the “left ventricular ejection fraction” (LVEF) — can help doctors assess heart function and determine treatment plans for cardiovascular disease.

Traditionally, LVEF is determined using echocardiograms, which are ultrasound videos of the heart. A trained sonographer will assess LVEF based on the echocardiogram, and a cardiologist will then review the assessment and potentially adjust it.

This two-step process is necessary for accurate measurements, but it’s also tedious and time-consuming.

Echonet AI: In 2020, Stanford University researchers published a study detailing how they’d trained a deep learning algorithm, dubbed “Echonet,” to assess LVEF from echocardiogram videos.

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