PODCAST

The Health AI Brief

Stephen Auger

Decoding artificial intelligence for busy medical professionals

health & fitness medicine

All Episodes

4:05

Epic's New AI - A Crystal Ball for Medicine, or a...

The Health AI Brief ·

2025/10/29

Epic recently unveiled Comet, a new AI model trained on 118 million patient records to predict future health events. The scale is unprecedented, and its initial ability to outperform specialised models is a huge leap forward for clinical AI.But what is it really learning from our messy, real-world data? In this today's episode, we break down why Comet is a landmark achievement but also an important wake-up call. We explore the challenges of "semantic drift" and documentation artifacts,

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2:47

027 Curriculum learning - teaching an agent step-by-step

The Health AI Brief ·

2025/10/28

You can't teach an AI complex medicine by throwing it in at the deep end. Curriculum learning applies the principles of medical school to AI, training models on simple tasks before moving to complex ones. Find out why this matters for building safe and effective clinical AI.#HealthAI #DigitalHealth #ArtificialIntelligence #MachineLearning #CurriculumLearning #ClinicalAI #MedEd #MedicalPodcast #ai in medicine Music generated by Mubert https://mubert.com/renderhealthaibrief@outlook.com

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2:44

026 Exploration-Exploitation Dilemma

The Health AI Brief ·

2025/10/24

An AI, like a clinician, faces a constant choice: stick with the proven treatment or explore a novel approach? In this episode, we break down the 'exploration-exploitation' dilemma, a core concept in AI that has major implications for how we design and trust medical AI systems.#HealthAI #DigitalHealth #ArtificialIntelligence #ReinforcementLearning #ClinicalAI #MedEd #MedicalPodcast#ai in medicine Music generated by Mubert https://mubert.com/renderhealthaibrief@outlook.com

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5:48

AI That Speaks the Language of the Cell and...

The Health AI Brief ·

2025/10/22

Paper: Scaling Large Language Models for Next-Generation Single-Cell Analysis by Rizvi et alPaper link: https://www.biorxiv.org/content/10.1101/2025.04.14.648850v2This week we're covering recent research presenting C2S-Scale, a new model from researchers at Yale and Google that teaches Large Language Models the "language of the cell."By translating complex genomic data into "cell sentences," this AI can predict cellular behaviour, answer complex biological questions, and has even

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3:58

025 Reinforcement learning - rewards and punishments

The Health AI Brief ·

2025/10/20

How does an AI like ChatGPT learn to be so helpful? The answer is "Reinforcement Learning," a powerful method of learning through trial-and-error, rewards, and punishments. In this special extended episode, we break down how reinforcement learning works and explain RLHF, the key technique used to train the language models that are transforming our world.#ReinforcementLearning #RLHF #AIinHealthcare #MachineLearning #ClinicalAI #HealthTech #LLM #ChatGPT #MedicalEducation #MedEd #ai in medicine

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3:40

Charting a Course for Safe AI in Medicine to Prevent...

The Health AI Brief ·

2025/10/18

We are rolling out powerful AI tools in hospitals and clinics at a breathtaking pace. But are they helping, or are they causing harm? A new report from the JAMA Summit on Artificial Intelligence reveals a key gap in our ability to answer that question. Featuring a stark warning from former FDA Commissioner Robert Califf, this episode breaks down why we are "flying blind" and explores the report's four-part blueprint to build a trustworthy and effective AI ecosystem. It's a call to

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3:16

024 Efficient Learning and Smart Shortcuts for...

The Health AI Brief ·

2025/10/16

Why build an AI model from scratch when you can give it a head start? And why waste expert time on easy cases? This episode explores two powerful strategies for efficient AI development. Discover how Transfer Learning gives your model a foundation of pre-existing knowledge and how Active Learning creates a smart feedback loop where the AI asks for help on only the toughest cases.#HealthAI #MedicalAI #TransferLearning #ActiveLearning #MachineLearning #AIinMedicine #DataEfficiency #HealthTech #ai in

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4:20

023 Self- and Semi-Supervised Learning - Learning...

The Health AI Brief ·

2025/10/14

How can an AI learn to read a medical scan without a perfect, expert-labeled dataset? In the real world, data is messy. This episode dives into three ingenious techniques (semi-supervised, self-supervised, and weak supervision) that allow AI to learn from a little bit of expert guidance, teach itself from unlabeled data, or make sense of noisy, imprecise information.#HealthAI #MedicalAI #SemiSupervisedLearning #SelfSupervisedLearning #WeakSupervision #MachineLearning #DataScience #DigitalHealth #ai

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4:40

An AI Doctor Takes on the NEJM: Dr CaBot, the...

The Health AI Brief ·

2025/10/10

The New England Journal of Medicine just featured an AI, 'Dr. CaBot,' as a guest expert in its legendary diagnostic challenge. This AI can not only find the right diagnosis but can reason and tell a compelling clinical story, sometimes more convincingly than human doctors.But does this mean Dr. AI is ready for the ward? We explore the gap between a perfect, curated case and the messy reality of clinical practice, and make the case for the future of AI not as an oracle, but as a

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2:50

022 Unsupervised learning - finding the patterns we...

The Health AI Brief ·

2025/10/09

What if an AI could find patterns in patient data that we've never seen before? That's the power of "unsupervised learning", a type of AI that learns without an answer key. In this episode, we explain how this method works, and why it's a powerful tool for discovering new patient subtypes and advancing personalised medicine.#UnsupervisedLearning #AIinHealthcare #MachineLearning #ClinicalAI #HealthTech #PersonalizedMedicine #PrecisionMedicine #MedicalEducation #MedEd #ai in

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2:53

021 Supervised learning - like learning with flashcards

The Health AI Brief ·

2025/10/07

How do we teach an AI to read an ECG? The most common method is "supervised learning," which is a lot like using flashcards with a medical student. In this episode, we explain this fundamental concept and reveal the two critical questions you should always ask about the data to assess the quality of any medical AI model.#SupervisedLearning #AIinHealthcare #MachineLearning #ClinicalAI #HealthTech #MedicalAI #MedicalData #MedicalEducation #MedEd #ai in medicine Music generated by Mubert

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5:09

AI Caught 'Cheating' Its Medical Exams - New Research...

The Health AI Brief ·

2025/10/04

Top AI models are acing medical benchmarks, but are they actually ready for the clinic? A groundbreaking study reveals that impressive scores can hide a dangerous lack of real-world robustness. In this episode, we break down the ingenious "stress tests" that expose how AI can succeed on an exam for all the wrong reasons—from guessing answers without seeing medical images to failing when the question format is slightly changed. Tune in to understand why we must move beyond leaderboard scores

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2:59

020 Hyperparameters - the AI's recipe

The Health AI Brief ·

2025/10/02

An AI model doesn't just learn on its own; it follows a protocol. The settings of that protocol, like the "learning rate", are called hyperparameters. In this episode, we explain what these crucial settings are, why they are the 'art' of AI development, and how they help you judge the quality of a research paper.#Hyperparameters #AIinHealthcare #MachineLearning #ClinicalAI #HealthTech #DataScience #DeepLearning #MedicalEducation #MedEd #ai in medicine Music generated by Mubert

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3:23

019 Learning rates and Gradient descent - finding the...

The Health AI Brief ·

2025/09/30

Imagine trying to find the lowest point in a valley while blindfolded. How would you do it? The same way an AI finds the best answer: one step at a time, always moving downhill. This process is called "gradient descent," and it's one of the engines that powers machine learning. In this episode, we explain how it works, what the "learning rate" is, and why it matters for understanding AI research.#GradientDescent #AIinHealthcare #MachineLearning #ClinicalAI #HealthTech

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4:01

The UK's New Health AI MHRA Commission - Rewriting...

The Health AI Brief ·

2025/09/29

The UK has just launched a star-studded National Commission to rewrite the rulebook for AI in the NHS. The goal: faster, safer innovation for patients. It could be a powerful accelerator and will hopefully avoid the pull of becoming another talking shop lost in bureaucracy.#HealthAI #AIinHealthcare #DigitalHealth #NHS #HealthTech #Regulation #MHRA #Innovation #MedTech #PatientSafety #FutureofHealthcare #UKInnovation#ai in medicine Music generated by Mubert

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3:11

018 The AI's Scorecard - What is a Loss Function

The Health AI Brief ·

2025/09/25

How does an AI model quantify a mistake? It uses a "loss function" – a scorecard that penalises different types of errors. In this episode, we explain what a loss function is, why it's not a one-size-fits-all tool, and how it reveals the true clinical priorities of any AI model. A crucial concept for critically appraising new research.#LossFunction #AIinHealthcare #MachineLearning #ClinicalAI #HealthTech #DigitalHealth #MedicalEducation #MedEd #CriticalAppraisal #ai in medicine Music

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2:09

017 How models actually learn

The Health AI Brief ·

2025/09/23

How does an AI model actually learn to spot disease on a scan? It all comes down to one fundamental goal: minimising error. In this episode, we kick off a new set of episodes on the mechanics of machine learning by explaining this core principle with a simple clinical analogy that will change how you look at AI. Understanding this is the first step to critically appraising any research paper that lands on your desk.#ArtificialIntelligence #AIinHealthcare #MachineLearning #ClinicalAI #AIinMedicine

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5:04

Forecasting Health with AI - A Deep Dive into the...

The Health AI Brief ·

2025/09/18

Shmatko, A., Jung, A.W., Gaurav, K. et al. Learning the natural history of human disease with generative transformers. Nature (2025).Link to paper: https://www.nature.com/articles/s41586-025-09529-3What if an AI could forecast your health like the weather? A groundbreaking new model called Delphi-2M, published in Nature, claims to do just that — predicting your risk for over 1,000 diseases using technology similar to ChatGPT.But is this the dawn of a new era in preventive medicine, or a high-tech

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5:44

AI in the NHS: A Reality Check on a National Rollout

The Health AI Brief ·

2025/09/17

We break down a landmark UCL study on the NHS's £21m programme to deploy AI in chest diagnostics.They uncover the real reasons for significant delays, moving beyond the technology to the critical, real-world barriers: staff capacity, fragmented IT infrastructure, and complex governance. Find out why dedicated project management is the secret to success and what this means for the future of AI in healthcare.Essential listening for any clinician, manager, or policymaker involved in digital

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3:45

016 DICOM, HL7, FHIR: The Languages of Medical Data...

The Health AI Brief ·

2025/09/16

Ever been handed a patient's CT scan on a CD-ROM and wondered why medical systems struggle to communicate? The problem is that they need to speak the same language. This episode decodes the three essential standards of medical data exchange.We break down DICOM (the "courier package" for images), HL7 (the "digital fax machine" for classic hospital data), and FHIR (the modern "smartphone app" enabling a connected future). Understand these acronyms to better appraise AI

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