Clinical AIACADEMY
The learning path

MODULE 1 / 8

What AI Really Is (And Isn't): A Clinician's First Look

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Section 1 of 9

In this module

Topics to explore:

  • Describe how AI learns from data rather than rules or reasoning
  • Identify key differences between traditional software and machine learning
  • Recognise common misunderstandings about AI performance and reliability
  • Explain why clinical data quality critically affects AI safety
  • Articulate the clinician’s role in supervising and questioning AI output

Slide 1 – Why This Learning Path Exists

AI in healthcare is no longer future talk.
It's showing up in radiology suites, outpatient clinics, and EHRs.

But it's also showing up in marketing pitches, buzzwords, and black-box tools that clinicians are asked to trust.
This learning path explores how AI works, where it can fall short, and the questions clinicians can ask about its use—no coding needed.

🎬 Bonus Material

New to AI in medicine? Watch this short introduction covering AI, machine learning, deep learning, generative AI, and large language models — and what they mean for the future of clinical practice.

▶ Clinical AI Academy

A Brief Introduction to AI in Medicine

Covers AI, machine learning, deep learning, generative AI, and LLMs — with real clinical examples including histopathology diagnostics and automated clinical documentation.