To succeed at an AI startup, you have to be able to show your work and its value. During this episode, I am joined by Brigham Hyde, Co-Founder and CEO of Atropos Health, to talk about his app that gathers real-world evidence for healthcare. He is an entrepreneur, operator, and investor who is deeply immersed in the potential of data and AI. Join us as he shares his journey to creating Atropos Health, why he believes AI is important for healthcare, and the potential it holds to bridge the evidence gap. We discuss how the lack of diversity in healthcare data has impacted patient outcomes leading up to this point and explore some of the methods Atropos uses to get the most out of machine learning. We discuss the AI data-gathering process, how each setup is validated and adapted, and how he measures the impact of his technology. In closing, he shares advice for other leaders of AI-powered startups and offers his vision for the future impact of Atropos.

Key Points:

• Welcoming Brigham Hyde, co-founder and CEO of Atropos Health.
• His journey to creating Atropos Health after working in other medical AI arenas.
• Why AI is important for healthcare: the evidence gap.
• Atropos’s perspective on the role of real-world evidence.
• How the lack of diversity in healthcare data sets impacts patient outcomes.
• Methods Atropos uses to leverage machine learning to ensure that patient populations are supported.
• The data-gathering process.
• How the setup is validated and adapted according to need.
• Measuring the impact of the technology.
• Advice for other leaders of AI-powered startups.
• Where Brigham foresees the impact of Atropos in three to five years.

Quotes:

“At Atropos, we focus on the automation and generation of high-quality real-world evidence to support clinical decision-making with the dream of creating personalized evidence for everyone.” — Brigham Hyde

“We see the role of real-world evidence and observational research as a great way to supplement that gap.” — Brigham Hyde

“It's our ability to create that evidence, transparently show you the populations that are being used and the bias that is involved, and the techniques to remove that bias that are the key.” — Brigham Hyde

“You've got to be able to show how what you're doing works, that it's not biased, and that it's applicable to the health system you're working with, and it's got to be done in extremely high quality.” — Brigham Hyde

Links:

Brigham Hyde on LinkedIn

Brigham Hyde on X
Atropos Health
Atropos Health on LinkedIn

Atropos Health on X

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