2min chapter

AI Today Podcast: Artificial Intelligence Insights, Experts, and Opinion cover image

AI Today Podcast: AI and Healthcare – Interview with Vignesh Shetty SVP & GM Edison AI and Platform at GE Healthcare Digital

AI Today Podcast: Artificial Intelligence Insights, Experts, and Opinion

CHAPTER

Data Exhaust - The Secret of Data Science

Modern data science owes a lot of its success to harvesting what is called data exhaust rit data that would typically get discarded in an environment of high storage cost. Data has actually huge value in driving clinical and operation outcomes, Pacha says. "This then would act as a fuel for the air i fire," he adds.

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Because most of these principles have been built an enshine after having worked closely with the regulatory bodies, with the providers, with your various slafeholders. That's another key thing that i believe is work that will definitely help mitigate concerns around data privacy, data sovereignty, as well as overall, greater adoption high quality applications. We also have a secret, and that that secret really is that modern data science, i think, owes a lot of its success to harvesting what is called data exhaust rit data that is of little to seemingly no use to an organization, and that would typically get discarded in an environment of high storage cost. But we believe that data has actually huge value in driving clinical and operation outcomes. Because what we can do with that is use that to kick start low stakes experimentation without really worrying about real patient data, given that the cost of failures is bounded. The upside, though, is unbounded, because as you iterate, as you learn more, and as you sift the wheat from the shafts, you convert data exhaust to the equitent of data gold. And this day, this then would act as a fuel for the air i fire. Because, as you cannot know, the reason why we are at an inflection point for ar is because there's a combination of things happening in the right time, which makes it alsi. One, you sadtin, get a huge variety of data, some of which are from images. Pacha got to make shots complind gpar yre of this lot of regulation that we need to absolutely make sure we state compliant with fur. Thereis also data coming out of variables from censors, with remote patient mandering, met with the broader redoction of a virtual care all over the world, in part due to the pandemic ad also things like broader immedium or adoption, the proliferation of even the internite and cheaper hardware, things like cloud computing and obviously better allgot tem so all of this are really making a big difference to how you identify what data as useful, what data actionable, and thenow, what insites can you drive?

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