EDiR Session
EDiR 19 - AI-driven exam question generation for radiology
Lectures
1
Chairperson's introduction
05:00Laura Oleaga Zufiria, Barcelona / ES
2
Practical aspects of AI-assisted radiology exam question generation
10:00Lukas Lambert, Prague / CZ
3
Impact on radiology examination standardisation
10:00Fabian Stöhr, Mainz / DE
4
Ensuring fairness and bias mitigation in AI-generated exam questions
10:00Roman Klöckner, Lübeck / DE
5
The future of AI in exam preparation in radiology
10:00Benedikt Kämpgen, Würzburg / DE
6
Panel discussion: The future of AI in radiology exam preparation: opportunities and challenges
15:00Panel discussion: The future of AI in radiology exam preparation: opportunities and challenges
5 min
Chairperson's introduction
Laura Oleaga Zufiria, Barcelona / Spain
10 min
Practical aspects of AI-assisted radiology exam question generation
Lukas Lambert, Prague / Czechia
- To learn how AI tools can assist in generating radiology exam questions.
- To appreciate the potential of AI in enhancing exam preparation.
- To understand the impact of AI on radiology exam preparation.
10 min
Impact on radiology examination standardisation
Fabian Stöhr, Mainz / Germany
- To learn how AI can help tailor question difficulty.
- To appreciate how AI ensures an optimal balance of question difficulty.
- To understand the impact of AI on question difficulty management.
10 min
Ensuring fairness and bias mitigation in AI-generated exam questions
Roman Klöckner, Lübeck / Germany
- To learn how AI models can introduce bias in exam question generation.
- To appreciate strategies for ensuring fairness and diversity in AI-assisted question creation.
- To understand AI's ethical and practical challenges in radiology exam standardisation.
10 min
The future of AI in exam preparation in radiology
Benedikt Kämpgen, Würzburg / Germany
- To learn about the future of AI in radiology exam preparation.
- To appreciate the benefits and challenges.
- To understand the future developments needed.
15 min
Panel discussion: The future of AI in radiology exam preparation: opportunities and challenges