Expectations vs. Reality: Machine Learning in Digital Health

The COVID-19 pandemic has accelerated the digital transformation of healthcare, and consumer adoption of digital health tools has skyrocketed during this time. Significant barriers to interoperability have begun to be addressed with the CMS Patient Access Final Rule enforcing adoption of FHIR across payers and providers. With all of this significant change, you’d expect enormous progress in application of machine learning to digital health, right?! Well, reality is a bit different from these expectations. This talk will explore the opportunities and practical challenges of applying machine learning to digital health with case study examples.

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