NCT06456203

Trial of Artificial Intelligence for Chest Radiography

Artificial Intelligence for Chest Radiography: Impact on Economics, Patient Outcomes and Radiology Service Delivery

• Status: Not Yet Recruiting
• Phase: N/A
• Study type: Interventional
• Enrollment: 10,000 (estimated)
• Sponsor: Duke-NUS Graduate Medical School · Academic / Other
• Sex: All
• Age: 14 Years – 130 Years
• Healthy volunteers: Accepted

Summary

Randomized Clinical Trial of the impact of Chest radiograph AI-assisted triage and report generation upon clinical outcomes and an economic analysis of impact of AI decision support on radiology service delivery.

Detailed description

Randomized, prospective selection of patients. Control group involves radiologists reporting chest radiographs as per reference standard clinical workflow Intervention group involves radiologists assisted with AI reporting an AI-triaged worklist of chest radiographs using an AI report generation tool Clinical outcomes on patients are studied at pre-determined study endpoints, including time to discharge from the hospital and re-admission rates. Economic analysis on cost-avoidance from man-hours saved from report generation and triage.

Conditions

• Pneumonia
• Lung Cancer

Interventions

Type	Name	Description
DIAGNOSTIC_TEST	AI	Artificial intelligence triage and reporting system

Timeline

• Start date: 2024-10-01
• Primary completion: 2025-09-01
• Completion: 2025-12-01
• First posted: 2024-06-13
• Last updated: 2024-06-13