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AI in Healthcare Essentials
A short foundation course for anyone who needs to understand AI in healthcare without yet needing to lead an implementation. Four compact modules: what AI actually is, where it creates value, what can go wrong, and how to judge an AI claim.
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Module 1
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What AI actually is
Tell AI, machine learning, deep learning and generative AI apart — and decide whether a healthcare problem needs AI at all.
20 minAI vs ML vs deep learning vs GenAI · Predict vs generate · LLMs in plain terms
Module 2
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Where AI creates value in healthcare
The recurring places AI pays off: documentation, triage and prioritisation, imaging support, operations and patient communication.
20 minFive value zones · Clinical vs operational vs admin · Output vs real-world value
Module 3
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What can go wrong
Bias, drift, hallucination, over-trust and workflow mismatch — the failure modes every user should recognise.
20 minHallucination · Bias and unequal performance · Data quality and drift
Module 4
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How to judge an AI claim
A short, reusable set of questions to ask about any AI claim, demo or vendor slide.
25 minClaim → Evidence → Fit → Impact · The evidence ladder · Relevant vs vanity metrics