Dev and Doc: AI For Healthcare Podcast – Détails, épisodes et analyse

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

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For enquiries - 📧 Devanddoc@gmail.com

🎞️ 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

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

Dev And Doc are back ! Here we break down the biggest highlights of 2023, and AI predictions for 2024. Dev and Doc is a Podcast where developers and doctors join forces to deep dive into AI in healthcare. Together, we can build models that matter. 👨🏻‍⚕️Doc - Dr. Joshua Au Yeung - https://www.linkedin.com/in/dr-joshua-auyeung/ 🤖Dev - Zeljko Kraljevic https://twitter.com/zeljkokr 00:00 start 01:01 Intro, Advancing LLMs in healthcare 07:10 Ambient note documentation in Medicine 10:52 Meta LLaMa are the good guys ? 14:40 GPT store 19:40 Overhyped Google Gemini model 26:17 AGI again 29:05 6 big predictions Open source vs Closed source models 38:55 AI in healthcare- LLM clinical trials , AI drug discovery 42:05 end References GPT store- https://openai.com/blog/introducing-the-gpt-store Hugging face predictions- https://twitter.com/ClementDelangue/status/1729158744762626310 AI drug discovery (blog post to paper) - https://news.mit.edu/2023/using-ai-mit-researchers-identify-antibiotic-candidates-1220 Google AMIE blog - https://blog.research.google/2024/01/amie-research-ai-system-for-diagnostic_12.html The podcast 🎙️ 🔊Spotify: https://open.spotify.com/show/3QO5Lr3w4Rd6lqwlfKDaB7?si=e7915d844994403e 📙Substack: https://aiforhealthcare.substack.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 :) 🎞️ Editor- Dragan Kraljević https://www.instagram.com/dragan_kraljevic/ 🎨Brand design and art direction - Ana Grigorovici https://www.behance.net/anagrigorovici027d

We have conversations between doctors and developers exploring the potential of AI in healthcare Josh is a training Neurologist in the NHS, and AI researcher in St Thomas' hospital and King's College Hospital. He is also a PhD student at King's College London. Zeljko is an AI researcher and PhD student at King's College London, as well as a CTO for a natural language processing company.

In this episode, Dev and Doc sit down to discuss artificial general intelligence from the perspective of a neurologist and computer scientist. We dive into the current developments around AGI , the 2 controversial schools of thought, LLMs and neuroscience, and give hot takes about whether we will ever reach AGI. Dev and Doc is a Podcast where developers and doctors join forces to deep dive into AI in healthcare. Together, we can build models that matter. 👨🏻‍⚕️Doc - Dr. Joshua Au Yeung - https://www.linkedin.com/in/dr-joshua-auyeung/ 🤖Dev - Zeljko Kraljevic https://twitter.com/zeljkokr 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 :) 00:00 start 01:05 intro 03:46 two camps of AGI - Yann Lecun vs Geoffrey Hinton, Architecture vs Data 07:47 Do emergent capabilities of LLMs pose a threat to humanity? 08:45 Intelligence and AGI - neuroscience and computer science approach 16:59 LLMs vs the human brain 24:16 Do AIs need a human touch? - Intrinsic personalities, temperaments, motivations, joy and reward The podcast 🎙️ 🔊Spotify: https://open.spotify.com/show/3QO5Lr3w4Rd6lqwlfKDaB7?si=e7915d844994403e 📙Substack: https://aiforhealthcare.substack.com/ 🎞️ Editor- Dragan Kraljević https://www.instagram.com/dragan_kraljevic/ 🎨Brand design and art direction - Ana Grigorovici https://www.behance.net/anagrigorovici027d

De-identifying and anonymising PHI (protected/personal health information) in health records is one of the central pillars of AI success in healthcare. Without de-identified data we cannot share data between hospitals , train models confidentially, or safely create large language models. Live from new orleans, Dev and Doc are here to dive into this fascinating topic, as well as describe our experiences of building and deploying an AI model with over 99% recall for redaction of PHI. Dev and Doc is a Podcast where developers and doctors join forces to deep dive into AI in healthcare. Together, we can build models that matter. 👨🏻‍⚕️Doc - Dr. Joshua Au Yeung - https://www.linkedin.com/in/dr-joshua... 🤖Dev - Zeljko Kraljevic https://twitter.com/zeljkokr 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 :) 00:00 start 00:52 intro 2:10 what is PHI? Personal /private health information 7:00 approaches on de-identifying hospital records 9:55 the problem with over-redaction /anonymisation 11:33 using deep learning for anonymisation 14:13 our experiences building a over 99% recall model VS manual annotation 18:03 how to make a high performing model - the art of annotations 24:49 Dev and Docs annotation method (Zeljko et al.) 30:42 how do you prevent overfitting? 31:54 ensuring model performs in new hospital / environments 33:23 future 34:48 synthetic data The podcast 🎙️ 🔊Spotify: https://open.spotify.com/show/3QO5Lr3... 📙Substack: https://aiforhealthcare.substack.com/ 🎞️ Editor- Dragan Kraljević https://www.instagram.com/dragan_kral... 🎨Brand design and art direction - Ana Grigorovici https://www.behance.net/anagrigorovic...

What is the current state of healthcare in the UK, is it ethical for patients to use LLMs for their healthcare ? Dev and Doc is a Podcast where developers and doctors join forces to deep dive into AI in healthcare. Together, we can build models that matter. 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 00:25 Intro 01:25 A personal account of the current state of healthcare 05:18 Did the covid pandemic really make a difference? 08:30 The NHS elective waiting list - 7.7 million patients and counting 12:04 Ghost patients - a data conundrum 13:55 BBC hospital waiting time tracker, ambulance wait times 19:00 Using AI / NLP to tackle elective lists 19:50 Patients will use tech like LLMs and ChatGPT to self diagnose 22:00 Symptoms need to be explored 26:10 data distribution on the web is skewed 28:50 Is it permissible to use LLMs in healthcare? 32:35 Directions for the future 35:20 ending The podcast 🎙️ 🔊Spotify: https://open.spotify.com/show/3QO5Lr3w4Rd6lqwlfKDaB7?si=e7915d844994403e 📙Substack: https://aiforhealthcare.substack.com/ 🎞️ Editor- Dragan Kraljević https://www.instagram.com/dragan_kraljevic/ 🎨Brand design and art direction - Ana Grigorovici https://www.behance.net/anagrigorovici027d Refs BBC wait tracker - https://www.bbc.co.uk/news/health-59549800 NHS waiting list, health foundation- https://www.health.org.uk/waiting-list

As the AI safety summit nears in England, the UK positions itself as a leader in AI safety, but what does this mean? Is AI safety all about preventing doom for the human race ? 🤖Dev and doc👨🏻‍⚕️ are here to break down this fascinating topic. Dev and Doc is a Podcast where developers and doctors join forces to deep dive into AI in healthcare. Together, we can build models that matter. 👨🏻‍⚕️Doc - Dr. Joshua Au Yeung - https://www.linkedin.com/in/dr-joshua-auyeung/ 🤖Dev - Zeljko Kraljevic https://twitter.com/zeljkokr 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 :) 00:00 intro 01:28 Start 06:30 AI safety definition 10:21 AI safety vs AI regulation 13:05 UK positions itself as a leader in the AI safety summit (featuring Rishi Sunak) 15:50 AI safety summit - responsible scaling 16:50 what does this mean for an AI researcher? When should we slow down research? 19:40 Yann Lecunn- we will get nowhere by simply scaling. The transformer architecture will NOT lead to AGI 25:30 Tackling AI safety with model evaluation,red teams and ethical hackers 33:36 Trusts sharing data, federated learning platform, over-regulation 38:57 google already has all of your data 41:49 there is a lack of research on AI safety The podcast 🎙️ 🔊Spotify: https://open.spotify.com/show/3QO5Lr3w4Rd6lqwlfKDaB7?si=e7915d844994403e 📙Substack: https://aiforhealthcare.substack.com/ 🎞️ Editor- Dragan Kraljević https://www.instagram.com/dragan_kraljevic/ 🎨Brand design and art direction - Ana Grigorovici https://www.behance.net/anagrigorovici027d

🤖Dev and doc👨🏻‍⚕️ introduces large multimodal models. ✨ The potential of LMMs combining text and images seem limitless, but what's the catch? Dev and Doc is a Podcast where developers and doctors join forces to deep dive into AI in healthcare. Together, we can build models that matter. 👨🏻‍⚕️Doc - Dr. Joshua Au Yeung - https://www.linkedin.com/in/dr-joshua-auyeung/ 🤖Dev - Zeljko Kraljevic https://twitter.com/zeljkokr 00:00 start 00:32 intro 02:20 what is multimodality? And what are the potentials? 09:43 Large multimodal models paper deep dive (radiology) 18:43 paper deep dive 2 (pathology) 20:40 large multimodal models technical overview, exploration of other LMMs 31:40 Foundational models explanation 35:18 the model transparency index 36:20 Google PaLI-3, light weight models vs large Foundational models 43:04 Summary 44:15 the problems and work to be done for LMMs - hallucinations, inconsistencies, biases, security 49:20 A call for better evidence generation and trials with LMMs 53:00 final points - improving visual spatial recognition, thoughts for future The podcast 🎙️ 🔊Spotify: https://open.spotify.com/show/3QO5Lr3w4Rd6lqwlfKDaB7?si=e7915d844994403e 📙Substack: https://aiforhealthcare.substack.com/ 🎞️ Editor- Dragan Kraljević https://www.instagram.com/dragan_kraljevic/ 🎨Brand design and art direction - Ana Grigorovici https://www.behance.net/anagrigorovici027d

How should one get into AI and Health tech? Here Doc offers the top 5 tips. Are you someone who is looking into AI and health tech? Or someone who is already in the field ? Share your thoughts and journey with us! Dev and Doc is a Podcast where developers and doctors join forces to deep dive into AI in healthcare. Together, we can build models that matter. 👨🏻‍⚕️Doc - Dr. Joshua Au Yeung - https://www.linkedin.com/in/dr-joshua-auyeung/ 🤖Dev - Zeljko Kraljevic https://twitter.com/zeljkokr 00:00 start 00:25 intro 02:05 why do developers not want to get into healthcare (shock) 05:45 what does Dev and Doc love about healthcare 09:20 AI is a multiplicator ------- 5 tips to get into health tech / AI----- 10:32 how a doctor can get into AI 10:40 1.AI is a collection of many topics and skills 13:23 should I learn to code ? 15:25 2.Understanding your intention 26:20 3.find a project 28:30 4.Find a team 31:54 5.Perseverance References: - https://discord.com/invite/hugging-face-879548962464493619 [Huggingface] - https://discord.com/invite/Mw77HPrgjF [Chipro] - https://www.reddit.com/r/learnmachinelearning/ - https://www.datacamp.com/ - https://www.kaggle.com/ - https://www.coursera.org/ - https://www.youtube.com/@AndrejKarpathy