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