6 papers
Decoder-Free Supervoxel GNN for Accurate Brain-Tumor Localization in Multi-Modal MRI
Andrea Protani, Marc Molina Van Den Bosch, Lorenzo Giusti +6
Modern vision backbones for 3D medical imaging typically process dense voxel grids through parameter-heavy encoder-decoder structures, a design that allocates a significant portion…
Federation of Agents: A Semantics-Aware Communication Fabric for Large-Scale Agentic AI
Lorenzo Giusti, Ole Anton Werner, Riccardo Taiello +8
We present Federation of Agents (FoA), a distributed orchestration framework that transforms static multi-agent coordination into dynamic, capability-driven collaboration. FoA intr…
Federated GNNs for EEG-Based Stroke Assessment
Andrea Protani, Lorenzo Giusti, Albert Sund Aillet +9
Machine learning (ML) has the potential to become an essential tool in supporting clinical decision-making processes, offering enhanced diagnostic capabilities and personalized tre…
Feasibility Analysis of Federated Neural Networks for Explainable Detection of Atrial Fibrillation
Diogo Reis Santos, Andrea Protani, Lorenzo Giusti +3
Early detection of atrial fibrillation (AFib) is challenging due to its asymptomatic and paroxysmal nature. However, advances in deep learning algorithms and the vast collection of…
A Federated Learning Platform as a Service for Advancing Stroke Management in European Clinical Centers
Diogo Reis Santos, Albert Sund Aillet, Antonio Boiano +10
The rapid evolution of artificial intelligence (AI) technologies holds transformative potential for the healthcare sector. In critical situations requiring immediate decision-makin…
Towards Explainable Graph Neural Networks for Neurological Evaluation on EEG Signals
Andrea Protani, Lorenzo Giusti, Chiara Iacovelli +9
After an acute stroke, accurately estimating stroke severity is crucial for healthcare professionals to effectively manage patient's treatment. Graph theory methods have shown that…