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AI4Triage - Development of an Artificial Intelligence Based Methods for the Analysis of Triage Data
Artificial intelligence, and in particular Graph Neural Networks (GNNs), have shown enormous potential in the analysis of complex clinical data. Thanks to their ability to model relationships between variables, GNNs represent a significant evolution compared to traditional models, enabling better interpretation of medical information and supporting data-driven decision-making in complex contexts such as emergency medicine. The application of GNNs to clinical triage and to the prediction of length of stay can improve clinical efficiency by optimizing resource allocation and patient management. This observational study aims to evaluate the accuracy of predictions with respect to real clinical data, contributing to the development of advanced predictive tools to support healthcare decision-making processes.
Age
All ages
Sex
ALL
Healthy Volunteers
No
University of Catanzaro
Catanzaro, Italy
Start Date
November 1, 2025
Primary Completion Date
November 1, 2026
Completion Date
November 30, 2027
Last Updated
January 6, 2026
1,500
ACTUAL participants
Observation
OTHER
Lead Sponsor
University of Catanzaro
Collaborators
Data Source & Attribution
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