ESR Education Committee Session

ESR Education 20 - Enhancing radiology education with artificial intelligence (AI): from simulation to personalised learning

Lectures

1
Chairperson's introduction

Chairperson's introduction

05:00Michail Klontzas, Heraklion / GR

2
From pages to prompts: can AI replace the radiology textbook?

From pages to prompts: can AI replace the radiology textbook?

15:00Tugba Akinci D’Antonoli, Basel / CH

3
Smart skills: integrating AI into interventional radiology training

Smart skills: integrating AI into interventional radiology training

15:00Pierluigi Glielmo, Milan / IT

4
Trust, bias and the black box: teaching ethical AI use in radiology education

Trust, bias and the black box: teaching ethical AI use in radiology education

15:00Merel Huisman, Nijmegen / NL

5
Panel discussion: Will AI revolutionise radiology education or just repackage what we already know?

Panel discussion: Will AI revolutionise radiology education or just repackage what we already know?

10:00Panel discussion: Will AI revolutionise radiology education or just repackage what we already know?

5 min
Chairperson's introduction
Michail Klontzas, Heraklion / Greece
15 min
From pages to prompts: can AI replace the radiology textbook?
Tugba Akinci D’Antonoli, Basel / Switzerland
  1. To explore how AI-powered tools, including large language models and adaptive platforms, are transforming radiology education.
  2. To evaluate the advantages and limitations of AI-generated educational content compared to traditional textbooks.
  3. To envision future trends in radiology education influenced by AI advancements.
15 min
Smart skills: integrating AI into interventional radiology training
Pierluigi Glielmo, Milan / Italy
  1. To learn about the potential of AI-based simulators and augmented reality in interventional radiology training.
  2. To understand how AI can support image-guided interventions through real-time feedback and decision support.
  3. To identify key challenges and best practices for incorporating AI into interventional radiology training curricula.
15 min
Trust, bias and the black box: teaching ethical AI use in radiology education
Merel Huisman, Nijmegen / Netherlands
  1. To explore key ethical concerns related to the integration of AI in radiology education.
  2. To recognise the potential risks of over-reliance on AI in clinical decision-making.
  3. To identify effective strategies for teaching responsible and transparent AI use in radiology.
10 min
Panel discussion: Will AI revolutionise radiology education or just repackage what we already know?

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