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

December 31, 2025 updated by: Pietro Hiram Guzzi, University of Catanzaro

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

Intervention / Treatment

Study Type

Observational

Enrollment (Actual)

1500

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • Italy
      • Catanzaro, Italy
        • University of Catanzaro

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

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

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

What is the study measuring?

Primary Outcome Measures

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

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

University of Catanzaro

Collaborators

Azienda Ospedaliero Universitaria Renato Dulbecco

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

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

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

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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