Impact AI Digital Twins for Clinical Trials with Charles Fisher from Unlearn AI
What if AI could improve the outcomes of clinical trials by making them more efficient and reducing the number of patients receiving placebos? Well, today’s guest, Charles Fisher is here to tell us all about how his company, Unlearn AI, is creating digital twins to do just that! In this conversation, you’ll hear all about Charles' academic background, what made him decide to create Unlearn AI, what the company does, and how they work within clinical trials. We delve into the problems they focus on and the data they collect before Charles tells us about their zero-trust solution. We even discuss Charles’ opinions of how domain knowledge should be used in machine learning. Finally, our guest shares advice for leaders of AI-powered startups. To hear all this and even find out what to expect from Unlearn in the near future, tune in now!
Key Points:
- A rundown of Charles Fisher’s background and what led him to create Unlearn AI.
- What Unlearn does, what digital twins are, and why they’re important.
- How clinical trials work and how they are used within Unlearn.
- The kinds of data they use and how they tackle these clinical trials using machine learning.
- What a zero-trust solution is and how Unlearn guarantees that their results are accurate.
- Charles shares his thoughts on the role of domain expertise in machine learning.
- His advice for any leaders of AI-powered startups.
- What we can expect from Unlearn in the next three to five years.
Quotes:
“[Unlearn is] typically working on running clinical trials where we might be able to reduce the number of patients who get the placebo by somewhere like – 50%.” — Charles Fisher
“[Unlearn] can prove that these studies produce the right answer, even though they leverage these AI algorithms.” — Charles Fisher
“It's very difficult to find examples where you can actually have a zero-trust application of AI. I actually don't know of another one besides [Unlearn’s].” — Charles Fisher
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