Observation: there is no intervetiuons
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.
| Facility | City | Region | Status |
|---|---|---|---|
| University of Catanzaro | Catanzaro | Italy |
This page summarises publicly available registry data for informational purposes — not medical advice. Eligibility is determined by each study team; patients should discuss participation with their clinician.
View NCT07312968 on ClinicalTrials.gov ↗ ← All trials in Italy