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PODCAST

The Health AI Brief

Decoding artificial intelligence for busy medical professionals in just a few minutes. Every second counts. We provide high-yield AI insights for physicians, surgeons, and healthcare executives who need the signal without the noise.Stay ahead of the future of medicine with ultra-concise briefings on:Ambient Clinical Intelligence: Automating medical documentation and EHR workflows.Generative AI & LLMs: Practical applications of ChatGPT and medical-grade AI in the clinic.Agentic AI: The rise of

health & fitness medicine

All Episodes

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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4:00

015 - Training data vs validation data vs test data

The Health AI Brief ·

2025/09/11

How do we know if a medical AI has truly learned to spot disease, or just memorised the answers to its practice questions? The same way we evaluate a trainee: with a final, unseen exam.This crucial process involves splitting data into three sets: training data (the textbook), validation data (the mock exam), and test data (the final exam). In this episode of The Health AI Brief, we explain why this split is our best defence against overconfident AI, what 'overfitting' means for clinical

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3:34

014 Data annotation and labelling

The Health AI Brief ·

2025/09/09

How do you teach an AI to read a chest X-ray? The same way a consultant teaches a resident doctor on a ward round: you point, you trace, and you provide the correct answer.This is data annotation, the meticulous, human-led process of "teaching" an algorithm by labelling thousands of examples. In this episode of The Health AI Brief, we explain why the quality of this digital teaching is everything. Discover why you should always ask who did the labelling when reading a new study, how human

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5:11

AI stethoscopes research trial - press release vs...

The Health AI Brief ·

2025/09/02

The headlines were everywhere: a revolutionary AI stethoscope that could more than double the detection of heart failure in GP clinics. The reported results from the TRICORDER trial sound transformative. But what happens when you look beyond the press release?Was it truly the AI that improved diagnosis, or did the trial simply prompt more testing? With reports that 70% of clinics stopped using the device long-term, what does this mean for real-world feasibility? #HealthAI #DigitalHealth

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3:53

013 Data cleaning and preprocessing

The Health AI Brief ·

2025/09/02

A patient's record is a chaotic mix of notes, lab test results, and codes. We can navigate the mess, but how can an AI? The answer lies in data cleaning and preprocessing – the most critical, yet unglamorous, step in building medical AI.This episode of The Health AI Brief explains why this process is like meticulously preparing ingredients for a complex recipe. We break down the key steps - from handling missing values to standardising formats, and offers three essential takeaways for appraising

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3:55

012 Data Quality - Junk in, junk out

The Health AI Brief ·

2025/08/29

A critically high potassium result arrives for a patient who looks completely well. Your first instinct isn't to treat, but to question the sample. Should we be just as sceptical of the data behind medical AI?This episode of The Health AI Brief dives into the most fundamental rule of artificial intelligence: junk in, junk out. Dr. Stephen uses the classic example of a haemolysed blood sample to explain why an AI model is only as reliable as the data it’s trained on. Discover how flawed data can

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76 results

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