Joint Session of the ESR and EORTC

ESR/EORTC - Next-generation imaging: clinical trials and AI

Lectures

1
Chairpersons' introduction

Chairpersons' introduction

05:00Thomas Beyer, Vienna / AT, Frédéric Lecouvet, Brussels / BE

2
Large language models in radiology and beyond

Large language models in radiology and beyond

15:00Christian Blüthgen, Zürich / CH

3
How to validate AI in healthcare?

How to validate AI in healthcare?

15:00Daniel Pinto Dos Santos, Frankfurt / DE

4
AI in hybrid imaging

AI in hybrid imaging

15:00Thomas Beyer, Vienna / AT

5
AI for oncological follow-up

AI for oncological follow-up

15:00Andrea Schenk, Bremen / DE

6
Patient's perspective: collecting high-quality data to benefit the patient

Patient's perspective: collecting high-quality data to benefit the patient

15:00Caroline Justich, Vienna / AT

7
Panel discussion: Challenges and opportunities of AI in clinical trials

Panel discussion: Challenges and opportunities of AI in clinical trials

10:00Panel discussion: Challenges and opportunities of AI in clinical trials

5 min
Chairpersons' introduction
Thomas Beyer, Vienna / Austria
Frédéric Lecouvet, Brussels / Belgium
15 min
Large language models in radiology and beyond
Christian Blüthgen, Zürich / Switzerland
1. To understand the foundations of language modelling.
2. To learn about application scenarios of large language models in radiology.
3. To learn about current and future developments in multimodal deep learning.
15 min
How to validate AI in healthcare?
Daniel Pinto Dos Santos, Frankfurt / Germany
1. To understand the importance of careful validation of AI tools in the context of data drift and data shift.
2. To discuss potential approaches to post-market surveillance of AI tools.
3. To learn about potential pitfalls in human-machine interaction and their impact on AI tools.
15 min
AI in hybrid imaging
Thomas Beyer, Vienna / Austria
1. To learn about the potentials and caveats of AI in clinical HI.
2. To appreciate the promise of AI and the responsibilities of the HI user community.
3. To understand the role of AI in the entire workflow of HI (from data acquisition to data corrections and quantification, as well as data handling and prediction models building on HI).
15 min
AI for oncological follow-up
Andrea Schenk, Bremen / Germany
1. To learn about the potential benefits of AI for oncological follow-up.
2. To understand the role of AI in the workflow of tumour monitoring.
3. To discuss challenges and potential pitfalls when using AI in oncological patients.
15 min
Patient's perspective: collecting high-quality data to benefit the patient
Caroline Justich, Vienna / Austria
1. To acknowledge why the quality of data collected plays a major role for patients on the one hand but for all stakeholders on the other hand regarding environment, costs, optimisation, evaluation, usability and acceptance, safety, and treatment progress.
2. To understand what we can learn and copy from other industries successfully implementing AI and deep learning.
3. To address misleading AI use of patients like Google and ChatGPT and to use tools to build awareness to avoid this.
10 min
Panel discussion: Challenges and opportunities of AI in clinical trials

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