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Healthcare AI Learning
Structured, evidence-led training on artificial intelligence in healthcare: identify where AI can create value, evaluate the evidence, deploy responsibly and scale what works.
AI in Healthcare · Module 1
From AI Idea to Healthcare Impact
The bridge from Essentials: where healthcare AI value actually appears, how to read any proposal along the chain from problem to output to decision to action to outcome to value, four questions that screen a proposal out before a business case, actionability under real capacity, and stating a proposal as a falsifiable value hypothesis.
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Course overview Course catalogueMastery overview
AI Foundations
Core concepts: ML, deep learning, generative models.
Healthcare Data
EHR, imaging, notes, wearables, interoperability.
Evaluation
Metrics, calibration, external and prospective validation.
GenAI
LLMs, prompting, retrieval, agents, oversight.
Strategy & Economics
Prioritisation, portfolio, TCO, realised value.
Regulation
EU AI Act, MDR/IVDR, GDPR, EHDS, governance.
Implementation
Workflow redesign, pilots, adoption, go-live, scaling.
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1. From AI Idea to Healthcare Impact
Estimated 45 min
Four surfaces of value · Problem → output → decision → action → outcome · Four questions before any model · Actionability & capacity · Value hypothesis · What external results license locally
Work through Module 1 — From AI Idea to Healthcare Impact — and complete its exercises and assessment at 80%.
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