Artificial intelligence in radiology: the basics you need to know

July 15, 11:15 - 12:15 CEST

E³ 120-1
Introduction by the moderator
Georg Langs, Vienna / AT
E³ 120-2
A. Conventional machine learning vs deep learning
Marleen de Bruijne, Rotterdam / NL
Learning Objectives
1. To understand the difference between machine learning and deep learning.
2. To learn about the various conventional machine learning techniques.
3. To learn about pros and cons of conventional machine learning vs deep learning.
E³ 120-3
B. Training data for deep learning: what is needed?
Ben Glocker, London / UK
Learning Objectives
1. To understand how deep learning algorithms are trained.
2. To learn about methods to perform deep learning in case of limited training data.
3. To understand the limits of deep learning approaches.
E³ 120-4
C. Clinical applications of artificial intelligence (AI) in medical imaging
Nickolas Papanikolaou, Lisbon / PT
Learning Objectives
1. To learn about the current state of the art of AI applications in medical imaging.
2. To focus on the current challenges related to AI development and deployment in clinical conditions.
3. To understand how AI will transform medical imaging in the long term.
E³ 120-5
Live Q&A



Georg Langs

Vienna, Austria