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Video course · 14 chapters · 31 min · certificate

AI in Healthcare for Clinicians: Tools, Limits, and Safety

A clinician's map of AI: rule-based systems, fuzzy logic, search, machine learning, deep learning, computer vision, LLMs, generative and multimodal AI, and robotics, with what each means for safe clinical use.

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What you'll learn

  • Distinguish rule-based AI from machine learning
  • Explain supervised, unsupervised and reinforcement learning
  • Describe neural networks and computer vision in radiology
  • Explain LLMs and generative AI for clinical drafting
  • Understand foundation and multimodal models
  • Apply a complete framework for medical AI

Chapters

14 chapters · 31:05
  1. 2:00 01Basics Members AI in healthcare: two families The reality of AI in healthcare and its two families: rule-based systems and learning systems.
  2. 5:00 02Rule-based Members Expert systems and rules Rule-based AI calculates from formulas, like maximum heart rate = 220 minus age, but never learns.
  3. 1:50 03Rule-based Members Fuzzy logic Rules with shades of grey: fuzzy logic handles 'somewhat' instead of strict yes or no.
  4. 1:40 04Methods Members Search, optimization and ML Search algorithms check thousands of options fast without learning; machine learning learns rules from data.
  5. 2:05 05ML Members Supervised learning Learning from labelled clinical data, like a child learning 'cat' from examples.
  6. 2:20 06ML Members Unsupervised learning Finding natural groupings in unlabelled data, useful for discovering patient subgroups in research.
  7. 2:00 07ML Members Reinforcement learning Learning by trial and reward, and how it can find strategies in medicine.
  8. 1:35 08Deep learning Members Neural networks and deep learning Neural networks, inspired by the brain, power deep learning.
  9. 1:30 09Vision Members Computer vision and radiology Computer vision recognizes images, from photo search to AI-assisted radiology.
  10. 2:00 10Language Members NLP and LLMs Natural language processing and large language models read, translate and write clinical text.
  11. 2:00 11Gen AI Members Generative AI Machines that create text, images and voices; in clinics, AI drafts and the doctor approves.
  12. 1:30 12Models Members Foundation models Train once, reuse many times: foundation models fine-tuned for tasks like reading X-rays or drafting reports.
  13. 1:30 13Advanced Members Multimodal AI and robotics Multimodal AI combines images, text and more; robotics ranges from warehouse robots to surgical systems.
  14. 4:05 14Summary Members A complete AI framework Putting it together: a framework of AI types for clinicians, and the safety principle behind all of them.

Jobs this course suits

Our AI checked this course against 500 jobs; these get the most out of it. Each job links to its learning path.

PhysiciansVeterinariansPhysiotherapistsRadiographersNurse PractitionersNursesParamedicsPsychiatristsSurgeonsDental HygienistsPharmacistsChiropractors