Download program here
Learning goals:
After the workshop, participants will be able to:
- Discuss differences between supervised and unsupervised learning
- Evaluate main steps for designing and building an AI algorithm in order to assess algorithmic bias
- Identify uncertainty in the medical decision process
- Discuss potentials and current limitations of AI for medical decision support in clinical practice.
Dates: Friday, 24th June 2022 & Saturday 25th June 2022
Location: TranslaTUM, Munich & online
Scientific program:
Friday, 24 June 2022
| 13:00 – 13:15 | Welcome & Introduction | |
| 13:15 – 14:00 | AI-based classification in Medical Imaging | Daniel Truhn |
| 14:00 – 14:45 | Using AI on Clinical Data: Best Practice and Important Pitfalls | Florian Hinterwimmer |
| Break | ||
| 15:15 – 16:00 | Explainable AI | Mauricio Reyes |
| 16:00 – 16:45 | AI-based Medical Decision Support in Pathology | Peter Schüffler |
| 16:45 – 17:30 | Anomaly Detection in Neuroradiology | Benedikt Wiestler |
| Break | ||
| 18:00 – 18:45 | Keynote: Safety nets for clinical deployment of medical imaging AI | Ben Glocker |
| 18:45 – 20:00 | Social Event @TranslaTUM |
Saturday, 25 June 2022
| 09:00 – 09:45 | Algorithmic Bias: what it is and why it is important | Christoph Haarburger |
| 09:45 – 10:30 | Clinical evaluation of Medical Decision Support in Neuroradiology | Dennis Hedderich |
| Break | ||
| 11:00 – 11:45 | AI in Ophthalmology | Hrvoje Bogunovic |
| 11:45 – 12:30 | Privacy-preserving and federated learning approaches | Georgios Kaissis |
| Break | ||
| 13:30 – 14:15 | AI in Dermatology | Alexander Zink |
| 14:15 – 15:00 | AI in Lung Imaging | Johannes Rückel |