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AI4Triage - Development of an Artificial Intelligence Based Methods for the Analysis of Triage Data.
Sponsor: University of Catanzaro
Summary
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.
Official title: AI4Triage - Development of an Artificial Intelligence Based Methods for the Analysis of Triage Data
Key Details
Gender
All
Age Range
Any - Any
Study Type
OBSERVATIONAL
Enrollment
1500
Start Date
2025-11-01
Completion Date
2027-11-30
Last Updated
2026-01-06
Healthy Volunteers
No
Conditions
Interventions
Observation
there is no intervetiuons
Locations (1)
University of Catanzaro
Catanzaro, Italy