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Trustworthy by Design: Ethics, Practice, and Impact of AI in Cancer Research and Care

28 October @ 14:00 - 15:30 CET

Trustworthy by Design: Ethics, Practice, and Impact of AI in Cancer Research and Care

Description:

Trustworthy AI has become a central concept in the ethical development and application of artificial intelligence in medicine. In cancer research, particularly in imaging, the potential of AI to improve diagnostics, treatment planning, and patient outcomes is immense. But what does it mean for AI to be truly trustworthy in practice?

This webinar brings together experts working at the intersection of AI development and cancer care to discuss practical dimensions of trustworthy AI. Topics will include current applications, perceived benefits, and challenges in clinical environments, as well as the role of human involvement, knowledge-sharing, and trust-building in real-world settings. The discussion will explore how to ensure that AI tools are not only reliable but also accepted and used with confidence.

The session will highlight concrete aspects to make AI in cancer research more inclusive, responsible, and impactful—supporting both patients and professionals in high-stakes medical decisions. Join us for an open and practice-oriented dialogue on how to foster trust in AI for cancer research and care.

Registration via Zoom: https://cesnet.zoom.us/webinar/register/WN_JAV88wUGTVKrdtk49sy0fw

 

Invited Experts:

Dr. Maciej Bobowicz (Medical University of Gdańsk)

Dr Maciej Bobowicz is an Assistant Professor at the 2nd Department of Radiology, Medical University of Gdańsk, Poland, and a surgical oncologist specialising in breast cancer diagnostics and treatment. His research focuses on the ethical and clinically responsible use of artificial intelligence in oncology, radiomics, and precision medicine.

He leads or contributes to several EU-funded projects, including EuCanImage, RadioVal, MAYA, Cinderella, TRACE and CAREWAY. He is also part of the AI4HI network, which supports the EUCAIM initiative under Europe’s Beating Cancer Plan. Author of over 80 scientific papers, Dr Bobowicz is committed to advancing patient-centred, trustworthy, and equitable AI applications in cancer imaging and care.

Prof. Karim Lekadir (University of Barcelona)

Karim Lekadir is an ICREA Research Professor in the Department of Mathematics and Computer Science at the University of Barcelona. He obtained his PhD from Imperial College London and was a postdoctoral researcher at Stanford University. He investigates new data science techniques for trustworthy and ethical artificial intelligence in medicine. He has been PI in 15 EU-funded projects, coordinated 6 Horizon projects, and was awarded an ERC Consolidator grant to investigate new AI techniques tailored to resource-limited settings.

ModeratorMelanie Goisauf (BBMRI-ERIC)

Dr. Melanie Goisauf is an accomplished social scientist with a PhD in Sociology from the University of Vienna, where she graduated with honours. She also studied at the Royal Holloway University of London and completed the postgraduate program “Sociology of Social Practices” at the Institute for Advanced Studies (IHS) Vienna.With almost two decades of experience as researcher and lecturer at, amongst others, the Department of Science and Technology Studies and the Institute of Sociology of the University of Vienna, as well as at the University of Malta, Dr. Goisauf has established herself as a leading expert in her field. As senior scientist at BBMRI-ERIC she is involved in several research projects and serves on ethical advisory boards. Dr. Goisauf also leads the Ethics of AI Lab, which focuses on the ethical and social implications of artificial intelligence, and is in charge of the scientific coordination of the Horizon Europe project PERIFORMANCE.

Registration via Zoom: https://cesnet.zoom.us/webinar/register/WN_JAV88wUGTVKrdtk49sy0fw

Details

Date:
28 October
Time:
14:00 - 15:30
Event Categories:
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Organiser

BBMRI_ELSI
View Organiser Website

The website was co-funded within ADOPT BBMRI-ERIC, a project that has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 676550.
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