Displaying one Session

Clinical Focus Session
Moderator/s:
  • E. De Kerviler (Paris, FR)
  • T. Kroencke (Augsburg, DE)
Date:
Sat, Apr 10, 2021
Time (in CEST):
16:30 - 18:00

501.1 - Artificial intelligence in oncology

Presenter:
  • T. Clozel (New York, US)
Learning Objectives:
1. To understand the basic concepts and to learn the different clinical aspects of AI in oncology
2. To learn about the influence of AI in the decision making process
3. To appreciate the current evidence and the expectations regarding AI in oncology

501.2 - Artificial intelligence in IO: diagnostics and response evaluation

Presenter:
  • M. Ronot (Clichy, FR)
Learning Objectives:
1. To understand the basic concepts and to learn the different clinical aspects of AI in diagnostic radiology
2. To learn about the influence of AI in early cancer diagnosis and response evaluation
3. To appreciate the available AI tools in diagnostic onco-radiology

501.3 - Artificial intelligence in IO: response prediction and virtual tumour board assistant

Presenter:
  • J. H. Geschwind (Northbrook, US)
Learning Objectives:

1. To understand the basic concepts of prognostic and predictive biomarkers in IO

2. To learn where AI can help IO in predicting responses

3. To appreciate the value and pitfalls of using AI as a virtual tumour board assistant

501.4 - Artificial intelligence in IO: procedural guidance, robotics and augmented reality

Presenter:
  • L. Solbiati (Busto Arsizio, IT)
Learning Objectives:
1. To understand the basic concepts and to learn the different technical aspects of robotics in IO
2. To learn about the latest developments in robotics in interventional oncology
3. To appreciate the current evidence of robotics in interventional oncology

501.5 - The hype: artificial intelligence in interventional oncology - more artificial than intelligent?

Presenter:
  • J. Chapiro (New Haven, US)
Learning Objectives:
1. To understand the current limitations of AI in interventional oncology
2. To learn about the overhyping aspects of AI in interventional oncology
3. To appreciate the current lack of evidence on AI in oncology

501.6 - The promise: being an interventional oncologist in the age of artificial intelligence

Presenter:
  • B. J. Wood (Bethesda, US)
Learning Objectives:
1. To understand the limitations of robotics and AI in interventional oncology
2. To learn how further developments will influence indication of IO therapies
3. To learn how further developments will improve performance of IO therapies