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Researchers from KU Leuven and UHasselt demonstrated that personalized federated learning (PFL) can significantly improve predictions of disability progression in Multiple Sclerosis (MS). Using data from over 26,000 patients, the team developed novel approaches like AdaptiveDualBranchNet, balancing global collaboration with local adaptation. The work was made possible by the VSC’s high-performance infrastructure, enabling large-scale federated experiments.

How VSC’s hands-on training empowers researchers to innovate, backed by insights from Geert Jan Bex.

Functional dependencies describe strong relationships in relational databases, helping ensure data consistency and integrity. When data is incomplete or contains errors, approximate functional dependencies (AFDs) become essential to detect patterns that “almost hold.” This study evaluates multiple AFD measures, identifying effective methods for discovering hidden dependencies in real-world large-scale datasets.

The PIDGIN Project at Hasselt University combines pathology, biomedical sciences, oncology, and data science to improve lung cancer diagnosis through AI and high-performance computing. By digitizing tissue slides and analyzing them at the pixel level, researchers can detect patterns invisible to the human eye. With VSC’s Tier-1 infrastructure, the team achieves faster, more accurate, and reproducible diagnoses, paving the way for personalized treatments.

By: Armando J. Cruz-Laufer, Maarten P. M. Vanhove, Lutz Bachmann, Maxwell Barson, Hassan Bassirou, Arnold R. Bitja Nyom, Mare Geraerts,...

By: Silke De Vriendt, Emma Laporte, Berkehür Abaylı, Julie Hoekx, Florian Hermans, Diether Lambrechts, and Hugo Vankelecom The pituitary...

By the SIMID research group (UHasselt, UAntwerp) The SIMID (Simulation Models of Infectious Diseases) team is a highly interdisciplinary...