Evaluation of the Efficacy of Diagnostic Support Algorithms in Chest X-rays- LuAna Trial

Recruiting now · Not applicable

Conditions studied: Consolidation, Lung Injury, Pleural Effusion, Pneumothorax, Cardiomegaly, Edema Lung

In brief

This study aims to evaluate whether the use of AI as a physician support tool is associated with an increase in the detection rate of chest radiographic findings in adults with respiratory complaints, compared to diagnosis performed exclusively by doctors, without AI support. This is a cluster-randomized clinical trial, following the stepped wedge design, and adhering to the guidelines of the Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT). In this study, the Diagnostic Support Solution for Chest X-rays - LungAnalysis (LuAna), developed by the Hospital Israelita Albert Einstein (HIAE) within the PROADI-SUS Banco de Imagens, was used. The clinical trial will be conducted in multiple centers with a diverse population from the public health system, to ensure that the algorithms are validated across a broad demographic profile. The expected benefits are significant, providing greater security for patients, increasing doctors' confidence in interpreting chest X-rays, promoting efficiency and cost savings for healthcare services, and offering promising prospects for other AI applications in imaging diagnostics.

Key facts

Study ID
NCT06686251
Run by
Hospital Israelita Albert Einstein
People needed
1470
Starts
2026-01-05
Expected to finish
2026-12-01
Last updated by the study team
2026-02-02

Who can join

Age: 18 and older. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

You may not qualify if…

Where it is running

Full record on ClinicalTrials.gov

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