Earlier Diagnoses, Better Outcomes: The Promise of Clinical AI

What if AI didn’t replace clinicians, but actually helped them care more like humans?

In this episode of Health Tech Checkup, hosts Rachelle Galant and Perry Dimas sit down with Dr. Dacre Knight, Associate Professor of Medicine at University of Virginia and Medical Director of the UVA Health EDS Center, as well as host of the podcast Bendy Bodies.

The conversation dives into why complex conditions like Ehlers-Danlos Syndrome are frequently misdiagnosed, and how augmented intelligence can surface hidden patterns across fragmented care. Instead of replacing physicians, AI may finally help connect years of scattered records, recognize longitudinal trends, and support earlier diagnoses, reducing the exhausting diagnostic journeys many patients face.

They also tackle the biggest tensions in modern healthcare:

balancing automation with human connection, precision medicine with insurance limitations, and innovation with regulation. Ultimately, Dr. Knight explains why he’s optimistic: when used correctly, technology doesn’t distance clinicians from patients — it gives them the time and clarity to focus on what matters most.

In this episode, you’ll learn:

- Why AI should be considered “augmented intelligence,” not artificial intelligence

- How pattern recognition across years of medical data can shorten diagnostic delays

- Where fragmented care hurts patients and how technology can fix it

- The role regulation, payers, and clinicians play in scalable personalized medicine

- Why better tech could actually bring humanity back into healthcare

If you’ve ever wondered whether health tech will depersonalize care, this conversation argues the opposite.

‍

Subscribe to HealthTech Check Up to stay up to date on where tech meets care, and leave us a review if you’re enjoying the show!

‍

‍

‍