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Technology and Healthcare Collide to Bring Artificial Intelligence to the Medical World

By Motley Fool Staff - Mar 22, 2017 at 7:22AM

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Collaborations between tech titans and healthcare giants are changing the way data is used in medicine.

Every day, an incredible amount of data is produced in the world of healthcare. So, it's no wonder that the leaders of the artificial intelligence industry see this sector as ripe for disruption.

In this segment from Motley Fool's Industry Focus: Healthcare podcast, the team describes some of the extraordinary work being done by collaborative efforts between leaders in the technology and healthcare sectors.

A full transcript follows the video.

This podcast was recorded on March 15, 2017.

Kristine Harjes: What sort of collaborations are you seeing out there between the healthcare world and the tech world?

Simon Erickson: For sure, Kristine. If we step back and look at this at the 10,000-foot level, first of all, the total amount of data that's in the world is growing at 40% a year. It's basically doubling every two years. Which means, probably, by the time you're listening to this, the statistic is out of date.

Harjes: [laughs] That's insane.

Erickson: We're spending about 18% of our GDP on healthcare, some $3 trillion a year. And the number of people that are over 100 years old in our country will rise from about 2 million people today to about 10 million in the next 30 years. It's amazing, when you think about the challenges that are facing healthcare today. But, the foundation of this industry is still really based upon the same things, which is taking data, and pattern recognition. Doctors are running tests, they're diagnosing patients and they're making treatment plans. But the way that you're starting to see more and more collaboration and the blurring of the lines between healthcare and tech is, now we have these huge artificial intelligence platforms run by big companies like IBM (IBM 2.62%). You hear about Watson a lot in the news. Intel, Microsoft, and Google also have their own platforms. They're able to take a lot more information than any one company could by itself. And they're really providing the insights of what that means. For healthcare, that's able to better diagnose medical images and really develop better treatment options. It's the same blocking and tackling that the industry has always done, it's just they have a ton more information to base it off of now.

Harjes: Right. And what IBM's Watson is doing is really incredible. This is the same platform that got its fame from being on Jeopardy, the TV show. Now, it's doing all these different intriguing things. For example, IBM has a collaboration with the healthcare world to use Watson to make diagnoses and to look at the data in a high-level way, and do things that maybe the human mind couldn't.

Erickson: Yeah, absolutely. I think the big impact we're going to see in the next coming years -- now, AI is more of a service than a product, it's more of a patient-focused service. And I think that's going to enable this shift to what we're calling personalized healthcare.

Harjes: Absolutely.

Erickson: We're at the point today where we're harnessing and understanding all these use cases in the data from companies. I think the second step is going to be changing that rough data into useful information. And once we have that useful information, the really exciting third step will be to change reimbursement models, to change the overall system that's really going to focus more on outcomes and the patient's personalized healthcare.

Harjes: Right. We're just getting started trying to apply AI to healthcare. One quote that I wanted to share from Mark Cuban, who is the guy from Shark Tank, and also owns the Dallas Mavericks, he was at South By [Southwest], and was speaking on Sunday. He says, "The world's first trillionaires are going to come from somebody who masters AI and all its derivatives and applies it in ways we never thought of." That's what we're doing here, trying to apply it to different healthcare applications to improve patient outcomes, and try to see what we can actually do with all this information that's being collected.

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