AI’s ‘radical potential’ to personalize medicine using population data

AI in Healthcare May 19, 2020
Dave Pearson

Clinicians equipped with machine learning can, in theory, apply what works for one patient to the care of another—and another, and another—and so on.

Ideally, the subsequent patients end up receiving care that is both personalized to them and driven by ever-bigger big data. Meanwhile administrators and payers get care protocols with less variation and thus less cost.

Stated another way: “The radical potential of AI is that health systems no longer need to choose between personalization and scale.”

That’s the thinking of Benjamin Fels, who has a vested interest in seeing the technology from the perspective of an AI enthusiast: He’s CEO of the Seattle-based healthcare AI company Macro-Eyes.

And yet Fels has written a balanced and thoughtful piece...

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