Table 2 Short description of the contents of the AI curriculum divided over 3 days
Short contents | |||
|---|---|---|---|
1 | Basics underlying AI algorithms | Including training procedures and assessment of the quality of fit (e.g., hyperparameters, overfitting) | Day 1 |
2 | Fundamentals underlying AI algorithms | Assessment of accuracy, sensitivity, specificity, and other metrics of performance evaluation | Day 1 |
3 | Quantitative approaches | To understand image quality and its impact | Day 1 |
4 | Case presentations of use of AI in clinical research | Hypothesis versus data-driven approach, associations, and statistics | Day 2 |
5 | Case presentations of use of AI in clinical care | Screening, triage, personalized medicine, and limitations of AI | Day 2 |
6 | Overview of available commercial software | And their use cases | Day 3 |
7 | Demonstration of basic integration of AI | Commercially available software to daily clinical workflow | Day 3 |
8 | Discussions about billing, legal, and ethical issues | Group discussions about business models, insurance, law, and ethics | Day 3 |