11 papers
Towards Actionable Surgical Team Dynamics: from Teamwork to Counterfactual Annotations
Vincenzo Marco De Luca, Antonio Longa, Andrea Passerini
Modeling team interactions in high-stakes environments such as operating rooms is critical for understanding how coordination, communication, and individual behaviors shape team pe…
From Multimodal Observation to Interpretable Suggestions: Counterfactual Time-Expanded Relational Modeling of Surgical Teams
Vincenzo Marco De Luca, Antonio Longa, Giovanna Varni +1
In surgery, patient safety is threatened not only by technical issues but also by poor teamwork. However, existing surgical AI-based solutions focus mainly on visual workflow and t…
Rethinking GNNs and Missing Features: Challenges, Evaluation and a Robust Solution
Francesco Ferrini, Veronica Lachi, Antonio Longa +5
Handling missing node features is a key challenge for deploying Graph Neural Networks (GNNs) in real-world domains such as healthcare and sensor networks. Existing studies mostly a…
Actionable Real-Time Modeling of Surgical Team Dynamics via Time-Expanded Interaction Graphs
Vincenzo Marco De Luca, Antonio Longa, Giovanna Varni +1
Surgical team performance arises from complex interactions between technical execution and non-technical skills, including communication and coordination dynamics. However, current…
Boosting Team Modeling through Tempo-Relational Representation Learning
Vincenzo Marco De Luca, Giovanna Varni, Andrea Passerini
Team modeling remains a fundamental challenge at the intersection of Artificial Intelligence and Social Sciences. Although a variety of computational models have been proposed in t…
A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data
Raffaele Pojer, Andrea Passerini, Kim G. Larsen +1
Graph neural networks (GNNs) excel at predictive tasks on graph-structured data but often lack the ability to incorporate symbolic domain knowledge and perform general reasoning. R…