Short, illustrated lessons for students and teachers in medicine, nursing and the health sciences. Each has key terms, a figure, a worked case, a self-check, a task to try and full references. Version 1.1, written by the Mr Researcher team from the guidelines in this library.
Under expert review: nursing and health-informatics educators are reviewing these lessons. Spotted an error? Write to support@mrresearcher.com
Based on: WHO: Guidance on large multi-modal models, NIST Generative AI Profile (AI 600-1)
Read the lessonBased on: TRIPOD+AI, PROBAST+AI, WHO: Generating evidence for AI-based medical devices, Good machine learning practice: 10 guiding principles
Read the lessonBased on: WHO: Ethics and governance of AI for health, IMDRF: Good machine learning practice (N88), EU Artificial Intelligence Act
Read the lessonBased on: WHO: Guidance on large multi-modal models, ICMJE Recommendations, section on AI, GAMER, UNESCO: Guidance for generative AI in education and research
Read the lessonBased on: WHO: Guidance on large multi-modal models, NIST Generative AI Profile (AI 600-1), UNESCO: Guidance for generative AI in education and research, ICMJE Recommendations, section on AI
Read the lessonBased on: WHO: Ethics and governance of AI for health, UNESCO: Recommendation on the Ethics of AI, FUTURE-AI, ANA: Ethical use of AI in nursing practice
Read the lessonBased on: EU Artificial Intelligence Act, Council of Europe Framework Convention on AI, Oman: Public policy for safe and ethical AI, Abu Dhabi DoH: Responsible AI Standard, Saudi FDA: Guidance for AI/ML-enabled medical devices (MDS-G010)
Read the lessonBased on: GAMER, RAISE 2026, CHART, CONSORT-AI, TRIPOD-LLM
Read the lessonBased on: UNESCO: Guidance for generative AI in education and research, AMEE Guide 158: Ethical use of AI in health professions education, AAMC: Principles for responsible AI use in medical education, NLN: AI in nursing education (vision statement)
Read the lessonBased on: ANA: Ethical use of AI in nursing practice, DECIDE-AI, NAIL-G: Nursing AI literacy and governance framework, American Academy of Nursing: AI in health care
Read the lessonBased on: CHAI Responsible AI Guide (Assurance Standards Guide), WHO: Regulatory considerations on AI for health, IMDRF: Good machine learning practice (N88), FUTURE-AI
Read the lessonBased on: WHO: AI and evidence-informed policy, UN: Governing AI for Humanity (final report), EU Artificial Intelligence Act
Read the lessonOnline courses from WHO, UNESCO, the NHS, professional bodies and universities, grouped by cost. We do not run or endorse these courses and receive nothing from them. Prices, credits and availability were checked on 1 Nov 2026; confirm them with the provider before you enrol.
WHO’s six ethical principles for AI in health and how to govern AI.
One worked case of building ethics into an AI screening tool.
Putting UNESCO’s Recommendation on the Ethics of AI into practice.
AI ethics in nursing, generative AI and access to care, and nurse-led AI design.
Basics of AI and machine learning, ethics and law, and using AI in the health system.
Using generative AI safely at work and bringing it into services.
Some items may need an NHS account.
How AI works, ethics and regulation, putting AI in place and evaluating it, following the NHS AI capability framework.
Some items may need an NHS account.
General AI literacy: what AI is, and what it can and cannot do.
Practical uses of AI in everyday clinical work, taught in Arabic.
Available until 31 Dec 2026.
Hands-on use of generative AI in clinical work.
Run by a publisher that sells an AI product.
Clinical data and machine learning for risk prediction, diagnosis and disease progression.
Archived course.
How to judge whether a clinical AI tool is safe, fair and useful.
Practical and responsible use of large language model tools in health.
An overview of AI applications in health from a Gulf university.
Plain-language basics of AI for non-technical people.
What generative AI can do, its limits, and everyday uses.
Writing effective prompts for large language models.
Generative AI use cases and risks in health care.
Run by a technology company.
Recognising, critically evaluating and safely using AI in nursing care.
Clinical data, machine-learning basics, evaluation and a capstone project.
Hands-on models for diagnosis, prognosis and treatment.
Designing, presenting and implementing AI projects in health care.
Strategy and the business case for AI in health care.