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/. 👋 Hey! If you are enjoying our conversations, reach out, share your thoughts and journey with us. Don't forget to subscribe whilst you're here :) https://www.linkedin.com/build-relation/newsletter-follow?entityUrn=7216474068085026817 https://youtube.com/@DevAndDoc https://podcasters.spotify.com/pod/show/devanddoc https://podcasts.apple.com/gb/podcast/dev-and-doc-ai-for-healthcare-podcast/id1751495120 https://aiforhealthcare.substack.com/ 👨🏻‍⚕️Doc - https://www.linkedin.com/in/dr-joshua-auyeung/ 🤖Dev - https://twitter.com/zeljkokr 🎞️ Editor - https://www.instagram.com/dragan_kraljevic/ 🎨 Brand design and art direction - https://www.behance.net/anagrigorovici027d 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