Robert Miller from ConsenSys Health Reveals that Machine Learning Algorithms are Getting Better at Matching Patients’ Identities

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Robert Miller, Director of Product Management and Strategy at ConsenSys Health, an organization that leverages blockchain and machine learning for “sustainable and value-based” healthcare, recently talked about the “uniqueness” of healthcare-related data.
Miller also discussed the relationship between federated learning and went over the different challenges in the standardization of healthcare data.
As explained by Miller, healthcare data is some of “the only data that we have that is not autobiographical, but it’s biographical.” For instance, you can almost always see any piece of information in some way as healthcare-related information.
As noted in a blog post by Ocean Protocol:
“When you write a social media post or you’re on Amazon searching a product- you took an action and that generated some information. But in the context of healthcare, at least in the traditional context, it is a physician actually, that is taking down notes.” 
The blog post further explains:
“It is through their lens of the world of your action, their interpretations that generate your healthcare information. Even though it’s a super-sensitive, intimate [piece of] information about you — it’s always generated through the lens of another person. It’s biographical, not autobiographical. And that generates …

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