Five questions for Machine Learning & Data Analytics Lab (MaD Lab) at FAU – TEAM-X consortium partner
Why are you involved in TEAM-X as a consortium partner?
The Chair of Machine Learning and Data Analytics at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) (approx. 45 employees) brings many years of expertise in the development and application of wearable measurement systems (Wearable and Ubiquitous Computing), as well as machine learning and human-computer interaction with a focus on Digital Health. As a spokesperson for the TEAM-X project, I advocate for a future in which this personal health data is made available to patients so that they can use it in a self-determined way.
What is your task?
Within the framework of TEAM-X, the chair is working on the integration of multiple data sources into a personalised therapy evaluation. On the other hand, the distributed application of machine learning via the patient’s terminal devices (so-called federated learning) is being investigated in order to be able to evaluate personal health data for research while respecting individual privacy and data protection. Across these concepts, issues of acceptance will be considered to ensure that TEAM-X builds patient trust. Such an interdisciplinary team allows for consideration of different perspectives and holistic solutions.
What are the biggest challenges?
The acceptance and trust of the end users will be crucial for the implementation in practice. This is why we take a user-centred approach throughout the development cycle, ensuring that the needs of end users are taken into account. This includes not only the Digital Responsibility Goals, but also education and outreach about the often hidden strengths of personal health data and how patients can use it to their advantage.
What are the benefits of a Gaia-X compliant data room?
Gaia-X is a European initiative to create a secure, trustworthy and privacy-friendly data infrastructure. Patients can benefit from the Gaia-X compliant TEAM-X data room in the future by having the technical means to view their own health data and share it with others. This pioneering work lays the foundation for a single European health data space.
What inspires you about Gaia-X?
By creating a European initiative for data exchange, Gaia-X is an important piece of the puzzle for a European Health Data Space that will enable patients to access and share their personal health data with providers and researchers in the future. It is the widespread implementation and application of this scale that will enable groundbreaking progress in joint European care and health research.