Module 1 · AI in Healthcare Essentials

What AI actually is

After this module you can distinguish the major types of AI and explain in simple terms how they differ.

Concept

Four words, one family

These terms are used interchangeably in meetings. They are not the same thing — and the difference changes what you should expect.

Artificial intelligence

Any system that performs tasks we would call intelligent. Includes rule-based systems written by hand.

Machine learning

The system learns patterns from data instead of being given explicit rules.

Deep learning

Machine learning using large neural networks. Works well on images, signals, speech and text.

Generative AI · an application family

Generative AI is not a fifth layer underneath. It is a current application family built mostly on deep learning — models that produce new text, images or audio rather than a score or a label.

In healthcare

A sepsis alert rule written by a clinical committee is AI in the broad sense but not machine learning. A sepsis risk score learned from a decade of admissions is machine learning. A model reading chest X-rays is deep learning. A tool drafting the discharge letter is generative AI.

Sources & evidence · 3 sources

Consensus guidance from WHO, international reporting standards and peer-reviewed literature. Healthcare examples in this module are synthetic teaching cases.

Content reviewed: September 2026. Publication dates of the individual sources are shown in each citation.

World Health Organization. Ethics and governance of artificial intelligence for health. 28 June 2021.
WHO guidance on the ethical principles and governance expectations for AI used in health, including human oversight, transparency and accountability. It is guidance, not law.
Open source
World Health Organization. Regulatory considerations on artificial intelligence for health. 19 October 2023.
WHO's overview of what regulators look for in health AI: documentation, data quality, intended use, validation and post-market monitoring. Useful orientation; national and EU rules still govern.
Open source
Lekadir K, et al. FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcare. BMJ. 2025;388:e081554. doi:10.1136/bmj-2024-081554
A consensus guideline covering fairness, universality, traceability, usability, robustness and explainability across the AI lifecycle. Consensus guidance, not evidence that any specific tool is trustworthy.
Open source