Dev and Doc: AI For Healthcare Podcast

• #24 Significantly advancing LLMs with RAG (Google's Gemini 2.0, Deep Research, notebookLM)

  Dev and Doc - Latest News Dev and Doc - Latest News It's 2025, Dev and Doc cover the latest news including Google's deep research and notebook LM, DeepMind's Promptbreeder, and Anthropic's new RAG approach. We also go through what retrieval augmented generation (RAG) is, and how this technique is advancing LLM performance. 👋 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 :) Meet the Team 👨🏻‍⚕️ Doc - Dr. Joshua Au Yeung - LinkedIn 🤖 Dev - Zeljko Kraljevic - Twitter Where to Follow Us LinkedIn Newsletter YouTube Spotify Apple Podcasts Substack Contact Us 📧 For enquiries - [email protected] Credits 🎞️ Editor - Dragan Kraljević - Instagram 🎨 Brand Design and Art Direction - Ana Grigorovici - Behance Episode Timeline 00:00 Highlights 00:53 News - Notebook LM, OpenAI 12 days of Christmas 07:44 Change in the meta - post-training 11:34 Optimizing prompts with DeepMind Promptbreeder 13:20 Is OpenAI losing their lead against Google 16:45 Deep research vs Perplexity 24:18 AIME and oncology 26:00 Deep research results 30:20 RAG intro 33:14 Second pass RAG 36:20 RAG didn't take off 38:40 Wikichat 39:16 How do we improve on RAG? 41:11 Semantic/topic chunking, cross-encoders, agentic RAG 51:15 Google’s Problem Decomposition 53:32 Anthropic’s Contextual Retrieval Processing 56:07 Summary and wrap up References Cross Encoders Wikichat Google's Problem Decomposition Anthropic's Contextual Retrieval Google AIME in Oncology DeepMind's Promptbreeder

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• #23 Can OpenAI's GPT o1 solve complex medical problems?

  First Thoughts and Preliminary Insights into OpenAI's GPT o1 Strawberry in the Medical Domain With some expected and unexpected findings, we have a "bake off" between o1 and Doc to demonstrate how o1 fares with tricky medical scenarios. Disclaimer Obviously, don't use AI to diagnose or treat your medical problems. If you are unwell, please seek a medical professional (AI isn't good enough just yet :)). 👋 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 :) Contributors • 👨🏻‍⚕️ Doc - Dr. Joshua Au Yeung - https://www.linkedin.com/in/dr-joshua-auyeung/ • 🤖 Dev - Zeljko Kraljevic - https://twitter.com/zeljkokr Follow Us • 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/ For enquiries - 📧 mailto:[email protected] Team • 🎞️ Editor - Dragan Kraljević - https://www.instagram.com/dragan_kraljevic/ • 🎨 Brand Design and Art Direction - Ana Grigorovici - https://www.behance.net/anagrigorovici027d Timestamps • 00:00 - Start + Highlights • 01:28 - Intro, What is GPT o1? • 05:18 - What is "Reasoning" in o1? • 12:38 - Benchmarks: o1's Successes and Failures • 24:07 - o1 and Doctor Bake Off! • 24:21 - The Pregnancy Acid Test for LLMs • 26:23 - Clinical Coding • 30:06 - Tricky Patient Scenarios • 32:25 - Opioid Dose Conversions

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• #22 Explaining Explainable AI (for healthcare) with Dr Annabelle Painter (RSM digital health section Podcast)

  Dev and Doc is joined by guest Annabelle Painter, doctor, CMO, and podcaster for the Royal Society of Medicine Digital Health Podcast. We deep dive into explainability and interpretability with concrete healthcare examples. Check out Dr. Painter's Podcast here, she has some amazing guests and great insights into AI in healthcare! - https://spotify.link/pzSgxmpD5yb 👋 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 :) 👨🏻‍⚕️ Doc - Dr. Joshua Au Yeung - https://www.linkedin.com/in/dr-joshua-auyeung/ 🤖 Dev - Zeljko Kraljevic - https://twitter.com/zeljkokr LinkedIn Newsletter YouTube Channel Spotify Apple Podcasts Substack For enquiries - 📧 [email protected] 🎞️ Editor - Dragan Kraljević - https://www.instagram.com/dragan_kraljevic/ 🎨 Brand design and art direction - Ana Grigorovici - https://www.behance.net/anagrigorovici027d Timestamps: 00:00 - Start + highlights 03:47 - Intro 08:16 - Does all AI in healthcare need to be explainable? 15:56 - History and explanation of Explainable/Interpretable AI 20:43 - Gradient-based saliency and heat maps 24:14 - LIME - Local Interpretable Model-agnostic Explanations 30:09 - Nonsensical correlations - When explainability goes wrong 33:57 - Modern explainability - Anthropic 37:15 - Comparing LLMs with the human brain 40:02 - Clinician-AI interaction 47:11 - Where is this all going? Aligning models to ground truth and teaching them to say "I don't know" References: Fun Examples of when models go wrong - Nonsensical correlations Mechanistic interpretability Anthropic - Mapping the mind of language models Limitations of current AI explainability approaches Explainability does not improve automation bias in radiologists

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• #21 Foundational Models in Digital Pathology: Enhancing Cancer detection and outcomes

  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

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• #20 How to build a successful healthTech/ BioTech start-up (2024 roadmap) - Derrick Khor

  Doc talks to Dr Derrick Khor - Cancer Doctor, HealthTech Consultant and Linkedin Guru. We share Derrick's insights from consulting over 120 companies and a step-by-step guide on how to build a successful Healthcare company. You can find more of Derrick and his helpful guides - https://adoptadoc.com/resources/ profile- https://www.linkedin.com/in/derrick-khor/ 👋 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 :) Dev&Doc is a podcast where doctors and developers deep dive into the potential of AI in healthcare. 👨🏻‍⚕️Doc - Dr. Joshua Au Yeung 🤖Dev - Zeljko KraljevicLinkedIn NewsletterYouTubeSpotifyAppleSubstack For enquiries - 📧 [email protected] <p>🎞️ Editor - <a href="https://www.instagram.com/dragan_kraljevic/">Dragan Kraljević</a></p> <p>🎨 Brand design and art direction - <a href="https://www.behance.net/anagrigorovici027d">Ana Grigorovici</a></p> Timestamps 00:00 Highlights and intro 3:01 Start 5:10 getting into health tech 8:03 lack of clinicians in start ups 15:07 Derrick's own healthtech journey to consulting 23:37 Start ups and failure 27:35 the start up road map 32:16 are you a medical device (samd)? Intended use 40:55 clinical evidence generation 48:16 go to market, NHS DTAC 57:57 power of networking, social media, linkedin 1:02:43 top UK health tech companies to look out for

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