AI4Triage - Development of an Artificial Intelligence Based Methods for the Analysis of Triage Data.

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.

Study Overview

• Status: Active, not recruiting
• Conditions: Triage
• Intervention / Treatment: Other: Observation

• Study Type: Observational
• Enrollment (Actual): 1500

Contacts and Locations

Study Locations

• Italy
  • Catanzaro, Italy
    • University of Catanzaro

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Child; Adult; Older Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

All individuals who request access to the ER will be duly considered.

Description

Inclusion Criteria:

• all

Exclusion Criteria:

• Patients labelled with red codes and serious injuries.

Study Plan

How is the study designed?

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Numbers of Undertriaged	The investigators will measure the number of misclassifications	12 monthds
Undertriaged	The investigators will measure the ability to predict undertriage	12 months

Collaborators and Investigators

• Sponsor: University of Catanzaro
• Collaborators: Azienda Ospedaliero Universitaria Renato Dulbecco

Study record dates

Study Major Dates

• Study Start (Actual): November 1, 2025
• Primary Completion (Estimated): November 1, 2026
• Study Completion (Estimated): November 30, 2027

Study Registration Dates

• First Submitted: December 17, 2025
• First Submitted That Met QC Criteria: December 17, 2025
• First Posted (Estimated): December 31, 2025

Study Record Updates

• Last Update Posted (Actual): January 6, 2026
• Last Update Submitted That Met QC Criteria: December 31, 2025
• Last Verified: December 1, 2025

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Investigative Techniques; Methods; Observation
• Other Study ID Numbers: AI4Triage

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: UNDECIDED

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No