2 citations · 3 across the 4 of their papers we have counts for
5 papers
Rethinking Fairness Metrics for Multi-Class and Multi-Group Assessment: Not Everything is Binary
Matteo Grazioso, Fabio Naccarella, Chiara Gallese +1
Artificial Intelligence, and Machine Learning in general, is becoming pervasive across all domains and disciplines. By means of this data-driven approach, algorithms can learns com…
Advancing Trustworthy AI in Healthcare Through Meta-Research: Results of an Interdisciplinary Design-Thinking Workshop
Valerie Bürger, Marlie Besouw, Jana Fehr +26
Meta-research and Trustworthy AI (TAI) share common goals, namely improving evidence, robustness, and transparency, yet there is very little interplay between the two fields. To in…
Multimodal Attention-Aware Fusion for Diagnosing Distal Myopathy: Evaluating Model Interpretability and Clinician Trust
Mohsen Abbaspour Onari, Lucie Charlotte Magister, Yaoxin Wu +10
Distal myopathy represents a genetically heterogeneous group of skeletal muscle disorders with broad clinical manifestations, posing diagnostic challenges in radiology. To address…
Measuring Perceived Trust in XAI-Assisted Decision-Making by Eliciting a Mental Model
Mohsen Abbaspour Onari, Isel Grau, Marco S. Nobile +1
This empirical study proposes a novel methodology to measure users' perceived trust in an Explainable Artificial Intelligence (XAI) model. To do so, users' mental models are elicit…
Assisting clinical practice with fuzzy probabilistic decision trees
Emma L. Ambags, Giulia Capitoli, Vincenzo L' Imperio +3
The need for fully human-understandable models is increasingly being recognised as a central theme in AI research. The acceptance of AI models to assist in decision making in sensi…