Education Hub

Learn AI.
Applied to medicine.

Webinar recordings, workshop slides, specialty AI resources, recommended reading, and the IAMSA curriculum framework — all in one place.

Webinar Recordings

National webinar series.

Monthly webinars covering AI across clinical specialties. All recordings available to IAMSA members free of charge.

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Coming Soon — June 2026
AI in Radiology: From Chest X-Ray to CT Triage Upcoming
National Webinar #1 · 60 min · Certificate of Attendance Included
RadiologyNHS AI ToolsClinical Practice
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Coming Soon — July 2026
AI in Pathology: Digital Slides and Diagnostic Automation Upcoming
National Webinar #2 · 60 min · Certificate of Attendance Included
PathologyDigital DiagnosticsHistopathology AI
❤️
Coming Soon — August 2026
AI in Cardiology: ECG Interpretation and Heart Failure Prediction Upcoming
National Webinar #3 · 60 min · Certificate of Attendance Included
CardiologyECG AIPredictive Medicine
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Coming Soon — September 2026
Large Language Models in Clinical Practice: Risks, Benefits, Evidence Upcoming
National Webinar #4 · 60 min · Certificate of Attendance Included
LLMsClinical Decision SupportSafety

Recordings become available to all members within 7 days of the live webinar. Join IAMSA free to access.

Workshop Slides

Regional workshop materials.

Slide decks from IAMSA workshops — ready to use at your institution with your regional lead.

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Introduction to Clinical AI — Slide Deck
45 slides · Beginner level · Updated June 2026
Members Only
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AI Ethics and Patient Safety in Clinical Settings
38 slides · All levels · Includes case studies
Members Only
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Reading an AI Research Paper — A Clinical Student's Guide
28 slides · Intermediate · Includes worked examples
Members Only
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NHS AI Lab — What's Deployed, Where, and Why
32 slides · All levels · NHS context essential
Members Only
Specialty AI Library

Resources by specialty.

Curated AI tools, papers, and explainers — organised by clinical specialty. Updated quarterly by the IAMSA Education Lead.

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Radiology & Imaging

Chest X-ray AI, CT triage tools, mammography screening, retinal disease detection. Tools: Annalise.ai, Viz.ai, BioMind.

12 Resources
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Pathology

Digital slide analysis, computational pathology, cancer grading AI. Tools: Paige.ai, PathAI, Ibex Medical Analytics.

8 Resources
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Cardiology

AI ECG interpretation, heart failure prediction, echocardiogram analysis. Tools: AliveCor, HeartFlow, Ultromics.

9 Resources
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Neurology & Psychiatry

Stroke detection AI, dementia biomarker analysis, mental health prediction models. Tools: Viz.ai LVO, Combinostics.

7 Resources
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Primary Care & GP

Sepsis prediction, medication reconciliation, risk stratification. Tools: Streams (Google DeepMind/NHS), EPIC Deterioration Index.

10 Resources
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Oncology

Cancer detection, treatment response prediction, genomics-driven AI. Tools: Tempus, Foundation Medicine, Flatiron Health.

11 Resources
Recommended Reading

Essential papers & books.

The IAMSA reading list — curated for clinical students with no prior AI background.

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Topol Review — Preparing the Healthcare Workforce to Deliver the Digital Future (2019)
NHS England · Foundational policy document · Free PDF
Read →
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High-performance medicine: the convergence of human and artificial intelligence — Topol (Nature Medicine 2019)
Nature Medicine · Landmark review · Open access
Read →
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A guide to deep learning in healthcare — Rajpurkar et al. (Nature Medicine 2019)
Nature Medicine · Technical but accessible · Open access
Read →
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Deep Medicine — Eric Topol (2019)
Book · Best accessible intro for clinical students · Available on Amazon
Recommended
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NHS AI Lab: A National Strategy for AI in Health and Social Care (2021)
NHSX · Policy · Free PDF
Read →
Curriculum Framework

The IAMSA AI
curriculum framework.

A structured, competency-based framework for AI education in medical schools — designed to be adopted by any institution.

01

Foundations of Clinical AI

Core concepts, terminology, and how AI tools are developed and validated for clinical use. No coding required.

  • What is machine learning? A clinical primer
  • How AI tools are trained, validated, and approved
  • Understanding sensitivity, specificity, AUC
  • Bias in clinical AI — causes and consequences
  • MHRA and FDA approval pathways for AI devices
02

AI Across Specialties

Specialty-specific AI tools and evidence — from radiology to primary care, with real clinical examples.

  • Radiology: chest X-ray, CT, mammography
  • Pathology: digital slides and cancer grading
  • Cardiology: ECG AI and heart failure prediction
  • Primary care: sepsis, deterioration, risk scoring
  • Oncology: genomics and treatment response
03

Ethics, Safety & Governance

The ethical, legal, and professional dimensions of AI in clinical practice — aligned with GMC guidance.

  • Algorithmic bias and health inequalities
  • Informed consent in AI-assisted decisions
  • Explainability and the black-box problem
  • Data governance: GDPR, NHS DSPT, ICO guidance
  • Professional accountability and the GMC position
04

Research & Critical Appraisal

How to read, appraise, and contribute to clinical AI research — including the TRIPOD+AI reporting framework.

  • Reading a clinical AI paper: a step-by-step guide
  • TRIPOD+AI and CONSORT-AI reporting standards
  • Systematic reviews in AI: challenges and methods
  • How to get involved in AI research as a student
  • IAMSA research working group pathway
Access Full Curriculum →