In May 2022, the Department of Diagnostic Radiology at Queen's University hosted a 3-week introduction to AI workshop. The workshop focuses on developing foundational literacy in AI for diagnostic radiology residents. The curriculum includes didactic lectures designed by a team of AI engineers and staff radiologist, case studies from literature, and programming examples highlighting data processing for AI analysis.
The curriculum was designed to follow specific learning objectives to introduce data science definitions, supervised and supervised learning, predictive analysis with machine learning, validation, requirements for clinical deployment, and introduction to modern techniques in deep learning.
All curricular content is available at our online repository, including learning objectives, lectures, and programming examples.
Visualization of a) curricular content and b) concepts highlighted in programming examples
For interactive programming, you can open our notebooks(.ipynb) directly in Google Colab from Github by just making one change.
Notebook(.ipynb) url:
Change it to:
