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Practical Machine Learning for Healthcare
Healthcare is often cited as one of the promising areas for machine learning. Healthcare workers are overwhelmed with large amounts of new data becoming available, but are often forced to use antiquated tools to manage that data and make decisions.

In this talk, Dave DeCaprio from ClosedLoop.ai will discuss some of the challenges to achieving the promise of machine learning in healthcare, along with some practical approaches he has used to overcome these challenges during his 15 years of data science work in the industry. In particular, Dave will cover how to communicate accuracy and demonstrate the real-world impact in healthcare, and how to address explainability for predictive models. Examples will be drawn from healthcare, but many of the lessons are generally applicable.

Who Should Attend

Some technical material will be covered, but the talk is targeted at both data scientists who create predictive models and the nontechnical stakeholders who are responsible for ultimately using them.

Aug 5, 2020 05:00 PM in Pacific Time (US and Canada)

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