An explainer on Foundation models for pathology, from Microsoft's Gigapath to Owkin's H-optimus-0, every company, big or small, are building pathology AI models. In this episode, Doc talks to Sean M. Hacking, assistant professor in Pathology at NYU Grossman School of Medicine and Özgür Şahin, particle physicist at CERN. Together they are building the infrastructure for digital pathology that then allows training of pathology foundational models. Find out more at https://www.pathonn.com/.

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00:00 Introduction

03:28 Why pathology

06:42 Transporting slides is a logistical nightmare

13:20 When particle physics and AI pathology collide

17:55 AI digital pathology - Patch-based architecture and sparse topologies

27:09 Is there enough pathology data?

29:11 Microsoft and Gigapath, transformer models for pathology

33:55 Pathology models clinical applications

43:18 Staining applications of AI

49:22 Building a digital pathology startup - Patho-NN

57:36 Using AI to see tumor grading features that humans can’t see


References:

https://www.nature.com/articles/s41586-024-07441-w

https://www.microsoft.com/en-us/research/blog/gigapath-whole-slide-foundation-model-for-digital-pathology/

https://www.nature.com/articles/s41379-021-00919-2