Héctor Cadavid

Héctor Cadavid, Hyunho Mo, Bauke Arends et al.

Cardiovascular disease (CVD) remains a leading cause of death, and primary prevention through personalized interventions is crucial. This paper introduces MyDigiTwin, a framework that integrates health digital twins with personal health environments to empower patients in exploring personalized health scenarios while ensuring data privacy. MyDigiTwin uses federated learning to train predictive models across distributed datasets without transferring raw data, and a novel data harmonization framework addresses semantic and format inconsistencies in health data. A proof-of-concept demonstrates the feasibility of harmonizing and using cohort data to train privacy-preserving CVD prediction models. This framework offers a scalable solution for proactive, personalized cardiovascular care and sets the stage for future applications in real-world healthcare settings.

Héctor Cadavid, Vasilios Andrikopoulos, Paris Avgeriou et al.

The problems caused by the gap between system- and software-level architecting practices, especially in the context of Systems of Systems where the two disciplines inexorably meet, is a well known issue with a disappointingly low amount of works in the literature dedicated to it. At the same time, organizations working on Systems of Systems have been developing solutions for closing this gap for many years now. This work aims to extract such knowledge from practitioners by studying the case of a large-scale scientific instrument, a geographically distributed radio telescope to be more specific, developed as a sequence of projects during the last two decades. As the means for collecting data for this study we combine online interviews with a virtual focus group of practitioners from the organization responsible for building the instrument. Through this process, we identify persisting problems and the best practices that have been developed to deal with them, together with the perceived benefits and drawbacks of applying the latter in practice. Some of our major findings include the need to avoid over-reliance on the flexibility of software to compensate for incomplete requirements, hidden assumptions, as well as late involvement of system architecting, and to facilitate the cooperation between the involved disciplines through dedicated architecting roles and the adoption of unifying practices and standards.