Defining Success in Healthcare AI: A Discussion with KLAS Research

After the “Peak of Inflated Expectations” set by vendors of black-box algorithms, healthcare organizations are now learning that building custom AI/ML models, tailored to specific member populations, is the key to success. But what does success look like, and how are organizations ensuring its realization?

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Defining Success in Healthcare AI: A Discussion with KLAS Research

Join Ryan Pretnik of KLAS Research and Andrew Eye, CEO of 2022 Best in KLAS Healthcare AI category winner ClosedLoop, to learn how healthcare organizations like yours are rapidly adopting new and custom AI to tackle some of healthcare’s big challenges.

You’ll learn:

- Why providers see greater accuracy and actionability with custom-built AI vs. “black box” models

- Why clinician trust and adoption of AI relies on more than model accuracy

- How accelerating custom healthcare AI led clients to give ClosedLoop A/A+ grades and a winning score of 96.5

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