The wider problem.

So chronic kidney disease is a billion person problem.

The prevalence is increasing double digits pretty much everywhere around the world.

The mortality is actually going in the wrong direction as well.

So probably in the 70s, mortality was like in the 36th in the world.

uh in the 1990s number 17 today it's number eight and by 2040 it's projected to be fourth and fifth right so you have a disease a billion people in the world increasing your prevalence mortality getting worse um the cost is to the healthcare systems is incredible it's one of the highest single line items So dialysis is very expensive, transplant are very expensive.

And in addition to the direct costs of dialysis, there are also indirect costs, caregiver time, transportation, lost productivity, lost taxation.

ThemePact.

In your experience and, and thoughts, how do you see AI fitting into this cardiorenal metabolic care landscape, and what excites or, or even concerns you most about its involvement?

What excites me about AI is that we are typically treating patients based on guidelines and treating them once they hit a certain threshold.

And the truth is that there are people with earlier stage disease that are more likely to progress rapidly.

And so using AI with good data from point-of-care testing and other sources of vital signs can really provide those insights in each community.

What that means is, for example, someone at stage two kidney disease, based on guidelines, they would say, "Well, come back in a year or two years, and we'll test you again." But AI, it may say that, "Hey, we are concerned about your risk of progression.

Even though you're early today, you're more likely to progress towards kidney failure." So it allows the doctors in that network to be more proactive and treat earlier.

Those are the positive things, uh, for AI.

Where do you see promising momentum right now?