Publikationen

Autor	Ahmad, Salmah; Bartelt, Bianca; Enzmann, Matthias; Kohlhammer, Jörn; Wesarg, Stefan; Wolf, Ruben
Datum	2026
Art	Conference Paper
Abstrakt	This paper presents MeDiTwin, a secure medical digital twin (MDT) platform designed to enhance patient data management within healthcare systems while ensuring robust data protection. As medical digital twins gain traction, their potential for enabling personalized treatment planning and advanced clinical research becomes increasingly evident. However, the inherent sensitivity of medical data requires strict adherence to EU General Data Protection Regulation (GDPR) standards, compelling the development of a platform that offers granular, patient-centric access control. MeDiTwin utilizes advanced cryptographic techniques, namely attribute-based encryption (ABE), to ensure data confidentiality and integrity during exchanges across institutional boundaries. The platform’s usability and feasibility are validated through expert feedback and structured user studies, which highlight its efficacy in managing complex medical data scenarios. This paper outlines the system architecture, usabili ty metrics, and insights from expert interviews, emphasizing the transformative potential of secure digital twin technologies in enhancing healthcare delivery while safeguarding patient autonomy and data security.
Konferenz	International Conference on Computer Graphics, Interaction and Visualization Theory and Applications 2026
Url	https://publica.fraunhofer.de/handle/publica/514119