Episódios
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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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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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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 -
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 Kraljevic
LinkedIn Newsletter
YouTube
Spotify
Apple
Substack
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>
Timestamps00:00 Highlights and intro3:01 Start5:10 getting into health tech8:03 lack of clinicians in start ups15:07 Derrick's own healthtech journey to consulting23:37 Start ups and failure27:35 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 DTAC57:57 power of networking, social media, linkedin 1:02:43 top UK health tech companies to look out for
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Dev and Doc deconstruct digital biomarkers! This is a fascinating and nascent field in the world of medicine, how have biomarkers transformed the way we practice medicine, and how will AI and wearables, sensors and digital fingerprints transform the way we practice in the future?
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 :)
find us on youtube- @Dev and Doc📙Substack: https://aiforhealthcare.substack.com/👨🏻⚕️Doc - Dr. Joshua Au Yeung - https://www.linkedin.com/in/dr-joshua-auyeung/🤖Dev - Zeljko Kraljevic https://twitter.com/zeljkokr🎞️ Editor- Dragan Kraljević https://www.instagram.com/dragan_kraljevic/🎨Brand design and art direction - Ana Grigorovici https://www.behance.net/anagrigorovici027d
Timestamp00:00 highlights01:50 intro02:40 how biomarkers evolved in the last century6:02 what is the definition of a biomarker10:00 biomarkers can be very biased depending on who you are testing12:31 when does a test become a biomarker17:30 the digital age and measurements - AI vision in retina scans, digital stethoscopes23:50 what is an “analog” biomarker vs digital biomarker?30:10 where do biomarkers fail in evidence based medicine?34:55 Biomarkers are pretty poor for mental health47:57 can AI predict depression better than humans? 51:21 Digital biomarkers to detect movement disorders 01:00:04 this can change clinical trials forever
Refs
- variable definitions of biomarkers https://informatics.bmj.com/content/31/1/e100914
-digital biomarkers convergence nature paper https://www.nature.com/articles/s41746-022-00583-z
-digital stethoscope for heart failure https://www.thelancet.com/pdfs/journals/landig/PIIS2589-7500(21)00256-9.pdf
-touch screen typing depression paper https://www.nature.com/articles/s41746-022-00583-z
- Duchennes body suit biomarker https://www.nature.com/articles/s41591-022-02045-1#Sec9
- Friedreichs ataxia body suit https://www.nature.com/articles/s41591-022-02159-6?fromPaywallRec=false#Sec9
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Dr Keith Grimes is a HealthTech consultant and General Practitioner working with companies to transform clinical ideas into something impactful. He worked as the digital health director in Babylon Health prior to its demise, and currently runs his own consulting firm, Curistica. This is one not to miss!ReferencesHealthTech consulting at Curistica www.curistica.com Prof Amanda Goodall on leadership theory https://amandagoodall.com/ For those interested in Leadership opportunities:-Faculty of medical leadership and management https://www.fmlm.ac.uk/-Bite labs https://www.bitelabs.io/ <p>Dev&Doc is a podcast where doctors and developers deep dive into the potential of AI in healthcare.<br>
👨🏻⚕️Doc - <a href="https://www.linkedin.com/in/dr-joshua-auyeung/">Dr. Joshua Au Yeung</a><br>
🤖Dev - <a href="https://twitter.com/zeljkokr">Zeljko Kraljevic</a><br>
<a href="https://www.linkedin.com/build-relation/newsletter-follow?entityUrn=7216474068085026817">LinkedIn Newsletter</a><br>
<a href="https://youtube.com/@DevAndDoc">YouTube</a><br>
<a href="https://podcasters.spotify.com/pod/show/devanddoc">Spotify</a><br>
<a href="https://podcasts.apple.com/gb/podcast/dev-and-doc-ai-for-healthcare-podcast/id1751495120">Apple</a><br>
<a href="https://aiforhealthcare.substack.com/">Substack</a><br>
For enquiries - 📧 <a href="mailto:[email protected]">[email protected]</a>
</p>
🎞️ Editor- Dragan Kraljević https://www.instagram.com/dragan_kraljevic/🎨Brand design and art direction - Ana Grigorovici https://www.behance.net/anagrigorovici027dTimestamps 00:00 start1:10 Career career career - GP, babylon health, digital consultancy6:40 working as a rural GP in Scotland9:21 time is the biggest factor of clinical impact12:11 finding impact through data 21:29 leading by example 23:52 Should doctors be leading healthtech businesses? 30:10 why do healthtech start-ups not have clinicians earlier? 36:30 Babylon failure - importance of having clinical influence at the top 43:55 experience being grilled on BBC newsnight 49:45 lessons learnt from the downfall of Babylon 52:25 6 values of consulting firm Curistica 55:51 common problems in start ups 59:36 how AI will change the healthcare landscape
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How do we reach the holy grail of a clinically safe LLM for healthcare? Dev and Doc are back to discuss news with Meta's LlaMA model and potential of healthcare LLMs finetuned on top like BioLlaMa. We discuss the key steps in building a clinically safe LLM for healthcare for healthcare and how this was pursued by Hippocratic AI's latest model - Polaris.
👨🏻⚕️Doc - Dr. Joshua Au Yeung - https://www.linkedin.com/in/dr-joshua-auyeung/
🤖Dev - Zeljko Kraljevic https://twitter.com/zeljkokr
The podcast 🎙️
🔊Spotify: https://podcasters.spotify.com/pod/show/devanddoc
📙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
References
Hippocratic AI LLM- https://arxiv.org/pdf/2403.13313
BioLLM tweet - https://twitter.com/aadityaura/status/1783662626901528803
Foresight lancet paper -https://www.thelancet.com/journals/landig/article/PIIS2589-7500(24)00025-6/fulltext
Linear processing units- https://wow.groq.com/lpu-inference-engine/
Timestamps
00:00 Start
01:10 Intro- llama3 , a chatGPT level model in our hands
06:53 Linear processing units to run LLMs
09:42 BioLLM for medical question and answering
11:13 quality and size of dataset, using youtube transcripts
12:41 Question and answering pairs do not reflect the real world - holy grail of healthcare llm
18:43 Dev has Beef with hippocratic AI
20:25 Step1 Training a clinical foundational model from scratch
22:43 Step 2 Instruction tuning with multi-turn simulated conversation
24:15 Step 3 training the model to guide model in tangential conversations
27:42 Focusing on the hospital back office and specialist nurse phone calls
33:02 Evaluating Polaris - clinical safety LLM , bedside manner, medical safety advice -
In this special episode we share a live recording of our live podcast episode at the Rewired UK conference, where NHS, industry and policy markers unite.
We discuss current LLMs from a technical and practical perspective. Dive into how to build Foundational models for the National health service and our experiences. We were also privileged to be joined by head of digital at Cambridge University Hospital NHS trust, Dr. Wai Keong Wong on how to evaluate AI products and discussions on automating administrative tasks for clinicians with ambient clinical documentation.
👨🏻⚕️Doc - Dr. Joshua Au Yeung - https://www.linkedin.com/in/dr-joshua-auyeung/
🤖Dev - Zeljko Kraljevic https://twitter.com/zeljkokr
The podcast 🎙️
🔊Spotify: https://podcasters.spotify.com/pod/show/devanddoc
📙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
00:00 intro
02:05 AI vs doctors - are language models ready to replace doctors?
05:22 the tranformer models and attention
08:51 human labour for reinforcement learning
11:00 building the NHS LLM, key concepts
13:55 foresight GPT - predicting the next clinical event in a patient timeline.
16:29 is text enough?
17:19 £3.8B investment into NHS digitisation and admin automation - ambient clinical documentation
20:14 how do you evaluate AI products for the NHS?
26:24 how do you vet the tech companies and future proof your purchase?
27:23 do clinicians need more digital health education?
28:41 transparency of AI models and benchmarks
31:30 question - EHR data created by AI leads to homogenisation and errors
34:03 question - training on structured vs unstructured EHR data
38:06 question - LLMs as a brain. How do we give it a body?
41:05 framework for ai deployment -
What do Prompt engineers have in common with telephone operators in the 1870s?
Spoiler - they're both dying professions
👨🏻⚕️Doc - Dr. Joshua Au Yeung - https://www.linkedin.com/in/dr-joshua-auyeung/
🤖Dev - Zeljko Kraljevic https://twitter.com/zeljkokr
The podcast 🎙️
🔊Spotify: https://podcasters.spotify.com/pod/show/devanddoc
📙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
00:00 Highlights
01:10 Intro - where did prompt engineering go wrong?
4:10 what is prompt engineering fundamentally?
10:54 LLMs training data reflects prompt engineering
12:32 prompts are model dependent
14:02 prompts that make you think
18:26 combining expert and generalist medical models for doctors
19:49 Diagnostic reasoning prompts, is it interpretable?
26:55 can we find prompts more elegantly/ systematically ?
28:42 Will prompts become obsolete? Models that self discover prompts
31:09 Telephone operators and Prompt engineers - death of a profession
Refs
Prompt "hacks" (oh man) - https://learnprompting.org/docs/intermediate/chain_of_thought
Diagnostic prompt interpretability paper - https://www.nature.com/articles/s41746-024-01010-1
self - discover https://arxiv.org/abs/2402.03620
telephone operators - https://www.history.com/news/rise-fall-telephone-switchboard-operators -
How do we align AI models for healthcare? 👨⚕️ And importantly, the moral codes and ethics that we practice everyday, how does the LLM deal with ethical scenarios like the trolley problem for example? This is a fascinating topic and one we spend a lot of time thinking about.In this episode Dev and Doc, Zeljko Kraljevic and I cover all the up to date topics around reinforcement learning, the benefits and where it can go wrong. We also discuss different RL methods including the algorithms used to train ChatGPT (RLHF). 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/zeljkokrThe podcast 🎙️🔊Spotify: https://open.spotify.com/show/3QO5Lr3...📙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_kral...🎨Brand design and art direction - Ana Grigorovicihttps://www.behance.net/anagrigorovic...00:00 Highlights01:27 start4:38 aligning ethics of ai models7:04 doctors ethical choices daily8:00 RLHF and AI training methods 16:29 reinforcement learning 19:35 Preference model -rewarding models correctly can make or break the success 27:05 exploiting reward function, model degradation (and how to fix it)RefAI intro paper - https://pn.bmj.com/content/23/6/476 Open AI RLHF paper - https://arxiv.org/abs/1909.08593 War and peace of LLMs! - https://arxiv.org/abs/2311.17227
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In this episode Doc goes on an adventure to chair an LLM/ generative AI conference session and reflects on his experience. Dev and Doc also discuss big news on meta's Llama3 and Code LlaMa.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/zeljkokrThe 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 Grigorovicihttps://www.behance.net/anagrigorovici027d00:00 Highlight00:36 Start 1:57 Are researchers just using Generative AI to get presentations /publications? 6:18 Hype cycles , lack of real world clinical studies using LLMs8:08 LlaMa3 , Code LlaMa announcement and insights 13:30 Google bard / Gemini ultra second on leaderboard 17:30 wrap up and end
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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/zeljkokr00:00 start01:01 Intro, Advancing LLMs in healthcare07:10 Ambient note documentation in Medicine10:52 Meta LLaMa are the good guys ?14:40 GPT store19:40 Overhyped Google Gemini model26:17 AGI again29:05 6 big predictions Open source vs Closed source models38:55 AI in healthcare- LLM clinical trials , AI drug discovery42:05 endReferencesGPT store- https://openai.com/blog/introducing-the-gpt-storeHugging face predictions- https://twitter.com/ClementDelangue/status/1729158744762626310AI drug discovery (blog post to paper) - https://news.mit.edu/2023/using-ai-mit-researchers-identify-antibiotic-candidates-1220Google AMIE blog - https://blog.research.google/2024/01/amie-research-ai-system-for-diagnostic_12.htmlThe 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 Grigorovicihttps://www.behance.net/anagrigorovici027d
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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.
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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/zeljkokrHey! 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 Data07:47 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 rewardThe 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 Grigorovicihttps://www.behance.net/anagrigorovici027d
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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 -
We start with a deep dive into why AI is required for the future of healthcare, and in what ways can AI be integrated. In the second part of the episode, we cover the VC involvement in the space and showcase the best use cases where AI companies can jump into healthcare.<p>Dev&Doc is a podcast where doctors and developers deep dive into the potential of AI in healthcare.<br>
👨🏻⚕️Doc - <a href="https://www.linkedin.com/in/dr-joshua-auyeung/">Dr. Joshua Au Yeung</a><br>
🤖Dev - <a href="https://twitter.com/zeljkokr">Zeljko Kraljevic</a><br>
<a href="https://www.linkedin.com/build-relation/newsletter-follow?entityUrn=7216474068085026817">LinkedIn Newsletter</a><br>
<a href="https://youtube.com/@DevAndDoc">YouTube</a><br>
<a href="https://podcasters.spotify.com/pod/show/devanddoc">Spotify</a><br>
<a href="https://podcasts.apple.com/gb/podcast/dev-and-doc-ai-for-healthcare-podcast/id1751495120">Apple</a><br>
<a href="https://aiforhealthcare.substack.com/">Substack</a><br>
For enquiries - 📧 <a href="mailto:[email protected]">[email protected]</a>
</p>
Timestamps:00:00 Start 00:20 Intro - Does AI need healthcare? 01:45 Definitions of AI 06:25 the current state of healthcare needs intervention08:14 are modern doctors spending more time with patients? 10:00 what can AI do for clinicians 15:59 AI super doctors! 22:09 will AI take over in our lifetimes? 23:38 industry paying attention, FDA, media, venture capital and businesses 26:20 barriers to patients getting right care Report segment - trying to bridge the gap from research to health tech companies /businesses 29:39 venture capital a16z report - "AI jobs to be done" 32:00 an ethical dilemma. When no doctor is available, Is it better to have a medical AI than no one? 37:12 low hanging AI fruit - Clinical coding /billing41:55 ai driven talk therapy 45:20 Psychology, Psychiatry, Neurology, segregated professions that should unite 47:10 other cases - scheduling patient appointments 51:20 ending References:https://www.sciencedirect.com/science/article/abs/pii/S0160791X23001264 https://www.bloomberg.com/news/articles/2023-09-01/tech-investors-bet-ai-finally-poised-to-transform-health-care?leadSource=uverify%20wallhttps://arxiv.org/pdf/2306.02022.pdfhttps://arxiv.org/pdf/2309.07430.pdf
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