[iancmceachern]

Yes, but they don't interpret it.

They aren't using AI or the cloud component to do what they can already do.

The whole promise that all these companies are pitching is to aggregate patient data over time, tie it to clinically measurable metrics so they can detect, prevent or treat things better. In your example the idea would be the model in the cloud is aggregating all the patient health record data, tying that to the xrays of those same patients, so that in the future the model can see things in x-rays that indicate disease or are predacessors to disease before we humans can even spot them.

All that takes money.

[hereme888]

Not quite the example I was explaining. In my example the validated/FDA-approved model runs on local hardware, at the physician's energy bill. Need an A6000 GPU? Fine, I'll buy it.

If the vendor wants to improve the model, they can ask for anonymized data from physicians, if they're willing to provide it. That's their cost of developing a better product, just like anyone in any industry pays a price in some way to improve their product.

[sciclaw]

A bit late here, but I thought I'd mention something in addition - most hospitals and doctors don't want to take on the burden or supporting something new and specialized. They will focus on providing care and buy support. Some have small IT departments, but even IT support is regularly contracted out.

[iancmceachern]

Your missing the details of why.

This stuff can't run locally, it's cloud connected by design. It's cloud connected by design because the company's value pitch is on the data, not the hardware. They loose money or break even on the capital hardware. This is always the case, intuitive makes their money on the instruments, others make it on the subscription fee.

If you want it this way, you'll end up paying a lot more for thr capital equipment.

There is no free lunch.