From Models to Medicine

What does emergency medicine have to do with large-scale knowledge systems? Jason Grafft joins us to talk about his non-linear path from EMS and simulation education to knowledge engineering and why the structured, fact-bound thinking that medicine demands is one of the most undervalued assets in the AI era. We dig into how he uses graph-based models to bridge clinical experts and technical system...

In this episode of From Models to Medicine, we sit down with Rachel Thomas to discuss the growing gap between AI hype and scientific reality in the life sciences. The conversation highlights the hidden costs of poor data quality and the necessity of domain expertise, featuring deep dives into real-world AI missteps, from a flawed enzyme classification paper to an app's mishandling of long-COVI...

As pathology labs digitize, how do skilled practitioners learn to trust AI with patient diagnoses? Michael Rivers discusses the critical importance of "explainable AI," keeping the human pathologist in the loop with the ability to override algorithms, and how these powerful new technologies will help address the global shortage of pathologists, ultimately bringing equitable, expert care to patient...

Join us in our first episode where we chat with Margo Georgiadis, CEO of Montai Therapeutics as we discuss what a model means in ML vs. life sciences and how she's been able to bridge the knowledge gap between these two practices for her team.

Welcome to From Model to Medicine , a podcast from KAMI Think Tank exploring how artificial intelligence is actually being applied across the life sciences industry. Each episode, we speak with scientists, operators, and leaders working at the intersection of AI and biology, from drug discovery and clinical development to regulatory operations and beyond. KAMI Think Tank is an educational organiza...