An observational study in Triage, sponsored by University of Catanzaro. Active, not recruiting at 1 site in Italy. Per ClinicalTrials.gov, last updated 2026-01-06.
Sponsored by University of Catanzaro · Observational
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.
University of Catanzaro is the lead sponsor of 43 studies on the registry; 2 are open to participants now.
Counted across the registry records on this site, refreshed daily.
All individuals who request access to the ER will be duly considered.
Exclusion Criteria:
there is no intervetiuons
Numbers of Undertriaged
The investigators will measure the number of misclassifications
Time frame: 12 monthds
Undertriaged
The investigators will measure the ability to predict undertriage
Time frame: 12 months
Plan to share: Undecided
No publications or documents are linked to this record.
This study is active, not recruiting, as verified in Dec 2025. You cannot join it, but the record below documents what was studied.
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University of Catanzaro