top of page

Panel discussion

Ethical implications of Big Data and AI in Biomedicine

Grow Your Vision

Welcome visitors to your site with a short, engaging introduction. 

Double click to edit and add your own text.


Dr. Dorothee Horstkötter

Head of the Department of Health, Ethics and Society, Maastricht University, the Netherlands.

Dorothee Horstkötter (PhD) is trained as a philosopher and ethicist and has specialized in Neuroethics, investigating ethical aspects that arise in the context of neuroscience, neuromodulation, (youth) mental health care and neurodegeneration. Her ethics research targets traditional modes of prevention and intervention, innovative (neuro)technologies and increasingly the implementation of digital care technologies and the usage of ai-supported tools. Her research focuses on ethical values like autonomy, responsibility, consent, justice, and equity, while she is also interested in the wider implications of emerging technologies on the meaning and scope of human agency and the normativity of human behavior and decision-making. Her work has been published in among others Neuroethics, Bioethics, The American Journal of Bioethics Neuroscience, Theory and Psychology, BioSocieties, Frontiers in Psychology, Journal of Alzheimer’s Disease, as well as in a series of book chapters and national journal articles. She is currently member of the EU-funded YouthGEMS consortium (Gene-environment interaction in mental health trajectories of youth), the Dutch Dementia Prevention Initiative (NDPI), and the Streamline consortium on modeling neurodevelopmental disorders. For many years, she teaches on ethical topics in several Bachelor and Master programs of FHML, currently developing a new course on neuroethics for the newly established Bachelor Brain Science.


Prof. Dr. Seppe Segers

Professor moral science and theoretical and practical ethics at the Department of Philosophy and Moral Science of Ghent University.

Prof. Dr. Seppe segers' main research domains are theoretical and substantive ethics, with a focus on normative and meta-ethics, and, respectively, bioethics, medical ethics and engineering ethics. He has published in academic journals and popular media about the use of AI in medicine, its ethical relevance, and questions using large language models in (medical) ethics. He is a member and former secretary of the Bioethics Institute Ghent and deputy of the Ethics and Law special interest group of the European Society of Human Reproduction and Embryology.


Dr. Stijn Denissen

Post-doc researcher at the AI-supported modelling in clinical sciences (AIMS) lab, VUB.

Stijn Denissen studied rehabilitation sciences at the KU Leuven after which he pursued a PhD in medical sciences at the VUB focusing on AI applications to study the link between structural brain MRI and cognitive impairment in multiple sclerosis. He is currently a post-doc at the AI-supported modelling in clinical sciences (AIMS) lab at the VUB continuing the federated learning project he started during his PhD. The concept enables training AI models on decentralised data sets, mitigating the need for data sharing between clinical centres.


Stijn is passionate about science communication, including converting papers to songs, and loves engaging in open science for reproducibility in AI research. In his free time, Stijn is a triathlete who loves reading, hiking, playing the violin, and listening to vinyl.


Prof. Dr. Rik Wehrens

Associate professor in the sociology of digital health at Erasmus School of Health Policy & Management.

Prof. Dr. Rik Wehrens has a background in the interdisciplinary field of Science & Technology Studies, combining perspectives from sociology (of science), anthropology and philosophy of technology. Working from a socio-technical approach that takes the intertwinement of technological and social developments as an analytical focus, his research work focuses on the various implications of the transformation to digital health for healthcare practitioners and patients. He utilizes ethnographic and discursive methods to analyze how data-driven technologies reconfigure knowledge practices, professional roles, and ethical decision-making in healthcare. Recent publications include papers in Social Science & Medicine, Big Data & Society, and Science, Technology, & Human Values.


Prof. Dr. Leonard Wee

Assistant professor of Clinical Data Science at Maastricht University

Prof. Dr. Leonard Wee specializes in using real-world clinical data generated from routine encounters of patients with the healthcare system, in order to generate new insights and testable clinical hypotheses. To do this, Leonard uses the Personal Health TRAIN (PHT) which is an open-source, demonstrably safe and proven ethical framework of performing federated learning, which means that mathematical models and statistical descriptions are shared but NOT any of the individual level patient data. To make this work, his research also focusses on how to make large volumes of data Findable-Accessible-Interoperable and Re-usable (FAIR) as well as artificial intelligence agents that analyse the distributed data on behalf of human researchers. Leonard is presently lead investigator or work leader across a number of multi-institutional and EU-funded federated learning studies.

bottom of page