Eric Topol

Is that a good way to summarize it?

Well, some people might know Chicago for deep dish pizza, but I know it for sensor pioneering work.

Yeah, and by the way, if you have questions that you want to ask, Shana, please put them in the message, and we'll try to make sure that we respond to them as we're talking.

Now, besides the consortium you have that has taken on this work,

You mentioned something that's really important is the AI side of it.

One of the most difficult things in AI is the analysis of data from continuous sensors.

The words that are used are time series analysis.

So in order, you know, there's so much data that's generated.

People think the genome has got a lot of data.

Well, you have a continuous sensors going on and you're trying to analyze that with all the other layers of a person data.

So have you been working on how to do that type of analytic work?

Because that's another part of the challenge.

Yeah, I couldn't agree with you more.

I mean, the ability to take the analytics to inform an individual about, you know, that they could be having impending heart failure, that they're having high levels of inflammation, that something is off track, you know, to have that do that reliably so they're not getting false signals, you know, it's another part of the challenge beyond what you've already done, which is really quite extraordinary.

Now, what's also amazing about you is that this is only one of the dimensions of your work.

I was looking at your recent publications and it is, you know, you've got all this work on rare cells, lymphocytes and macrophages.

You've got, you know, many different aspects of what you're doing that are apart from this.

So maybe you can just fill us in that this is just, maybe this is the principle part that's got you most excited, but you're using, because you have molecular probes, um,

you know, in the live person, or at this point, perhaps you say models, you're going in directions for intracellular delivery.

I mean, wow.