1. To learn about available supervised vs unsupervised machine learning techniques.
2. To learn about deep-learning methods to discover biomarkers.
3. To understand the strength, but also limits and pitfalls, of machine learning methods.
1. To learn about how COST actions work and the outputs generated.
2. To appreciate examples of a successful COST action for selecting imaging biomarkers.
3. To understand difficulties in selecting biomarkers for specific indications.
1. To learn about multimodality and hybrid imaging biomarkers combinations; are they worthwhile or worthless?
2. To appreciate what genomics has taught us in this area.
3. To understand how we can use AI to manage the imaging biomarker environment.