AI and machine learning have had a huge impact on the healthcare industry, but there are still plenty of advances to be made. Joining me today is Sam Rusk, Co-founder and CAIO of EnsoData, to talk about how their team is using machine learning to optimize sleep. Tuning in, you’ll learn about the founding of EnsoData, their implementation of ML, and the important role they play in the healthcare sector. We discuss the primary challenges of working with and training models on waveform data, EnsoData’s diagnostic processes, and how they use ML to process collected waveforms and identify therapy opportunities. Sam also shares his thoughts on how ML has developed since they first founded the company nine years ago, his advice for other leaders of AI-powered startups, and what his hopes are for EnsoData in the next five years. To learn how EnsoData is making waves in healthcare, be sure to listen in today!
Key Points:
Quotes:
“We have a pretty mature process for taking feature ideas and moving them from the top of the funnel on product management all the way to testing and releasing those.” — Sam Rusk
“We spend a lot of our time solving not necessarily the machine learning performance side of the problem, but more ‘how do we get this into the clinicians’ hands in a way that makes sense for everyone.’” — Sam Rusk
“While we want to deliver products that change the game, we [also] invest heavily in research, and we are active in the community, publishing and engaging in the research community in sleep.” — Sam Rusk
Links:
Sam Rusk on LinkedIn
EnsoData
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