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

Launched by HOSPITAL ISRAELITA ALBERT EINSTEIN · Nov 11, 2024

Keywords

ClinConnect Summary

The LuAna Trial is studying how well artificial intelligence (AI) can help doctors detect issues in chest X-rays for adults who have breathing problems. The main goal is to see if using AI alongside doctors increases the chances of finding important health issues, like lung injuries or fluid in the lungs, compared to doctors working alone without AI support. This trial will take place in various hospitals and clinics, ensuring that the AI tool is tested on a wide range of patients from different backgrounds.

To be eligible for this trial, participants must be over 18 years old and have chest X-rays taken while experiencing respiratory symptoms. The X-rays should show at least one clear frontal view of the chest. However, individuals who had their X-rays done for specific reasons like trauma or cancer screening will not be included. If you choose to participate, you can expect that the trial will focus on improving the way chest X-rays are interpreted, which could lead to better care and faster diagnoses for patients in the future.

Gender

ALL

Eligibility criteria

• Inclusion Criteria:
• • Non-reported chest X-rays (XRts) of individuals aged over 18 years.
• • Individuals images with respiratory complaints.
• • Chest X-rays taken during the presence of these respiratory symptoms or while being followed up for respiratory disease.
• • Chest X-rays taken on any X-ray machine.
• • Chest X-rays that include at least one frontal view of the chest.
• Exclusion Criteria:
• • Those whose chest X-ray was performed due to a history of trauma, pre-operative risk assessment, lung cancer screening, or exclusively for verifying the correct positioning of a peripheral intravenous catheter (PICC).
• • Chest X-rays with technical quality below the minimum required for proper interpretation and diagnosis.
• • Cases without at least one frontal view.
• • X-rays printed on regular paper.