Pierre Elias

An echocardiogram costs a few thousand dollars.

It's an hour-long procedure where they look at the heart in a bunch of different angles.

And so we end up in a situation where the way we diagnose cardiovascular disease is either too expensive or too invasive to do at a population level.

So we wait until patients oftentimes present with symptoms, which is late in their disease course, and patients have worse outcomes because of that.

Okay, so all you need to do is what then?

All you need to do is magically find a way to create a cheap, ubiquitous test that can screen for the most common cause of death in the world.

And I became obsessed with this.

I asked myself, well, is there anything that we're doing today that could fill that role?

And what I came up with was the humble electrocardiogram.

So if you've watched any medical drama and you see the squiggly lines in the background that go beep, beep, beep, that's an electrocardiogram where we measure the surface electrical activity of the heart.

If you have an Apple Watch, you can do a one lead electrocardiogram right now.

We are taught from medical school onwards that you cannot diagnose those diseases with an electrocardiogram.

It's simply taught as not possible.

But we asked ourselves, could AI do exactly that?

We built

one of our first AI models, and we were shocked to find that it worked really well.

We tested it on nearly 20,000 patients in a retrospective dataset, and we found this AI model could outpredict me in trying to find valvular heart disease from the electrocardiogram.

And then we asked ourselves, well, could we find all forms of structural heart disease

from an electrocardiogram.

And that set us off on this journey of the last five years, where we built this technology called Echo Next, which looks at an electrocardiogram and tells us, does this patient have structural heart disease or not?