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SkillsCast

Messy Data and Reluctant Users - The Trouble with Healthcare Data

4th July 2019 in London at CodeNode

There are 15 other SkillsCasts available from Infiniteconf 2019 - A one-day community celebration of Big Data, Machine Learning and AI

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This talk is neither about big data, nor about AI. It's about artisanal, handcrafted data that poses a real challenge for anyone trying to analyze it: healthcare data. In theory, applying AI to healthcare sounds like the perfect match - look at real world data generated by patients, apply AI, learn from trends, and improve healthcare outcomes based on those learnings. Systems like IBM Watson make us believe that the problem is already solved, but in reality, real world healthcare data and its applications suffer from problems not encountered in other domains, which poses huge challenges for any kind of analytical applications.

In this talk, Samantha will look at the landscape of messy and patchy healthcare data, understand the difficulties of drawing reasonable conclusions from the data, and discuss the challenges of changing user behavior in healthcare.

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Messy Data and Reluctant Users - The Trouble with Healthcare Data

Samantha Bail

After spending several years in Academia, Samantha became an early employee at Flatiron Health, a New York City healthcare technology startup. As a Senior Data Insights Engineer, she helped build up many of the company’s data products. Within only five years, she watched the organization grow from two dozen people to almost 700 employees and go through an acquisition by a large, multinational company.

SkillsCast

Please log in to watch this conference skillscast.

Https s3.amazonaws.com prod.tracker2 resource 41088130 skillsmatter conference skillscast o9nohu

This talk is neither about big data, nor about AI. It's about artisanal, handcrafted data that poses a real challenge for anyone trying to analyze it: healthcare data. In theory, applying AI to healthcare sounds like the perfect match - look at real world data generated by patients, apply AI, learn from trends, and improve healthcare outcomes based on those learnings. Systems like IBM Watson make us believe that the problem is already solved, but in reality, real world healthcare data and its applications suffer from problems not encountered in other domains, which poses huge challenges for any kind of analytical applications.

In this talk, Samantha will look at the landscape of messy and patchy healthcare data, understand the difficulties of drawing reasonable conclusions from the data, and discuss the challenges of changing user behavior in healthcare.

YOU MAY ALSO LIKE:

Thanks to our sponsors

About the Speaker

Messy Data and Reluctant Users - The Trouble with Healthcare Data

Samantha Bail

After spending several years in Academia, Samantha became an early employee at Flatiron Health, a New York City healthcare technology startup. As a Senior Data Insights Engineer, she helped build up many of the company’s data products. Within only five years, she watched the organization grow from two dozen people to almost 700 employees and go through an acquisition by a large, multinational company.

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