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An Explainable Neuroradiologist Artificial Intelligence Assistance System for Brain CT and MRI
Sponsor: Yaou Liu
Summary
This clinic trial aims to validate the working performance of radiologists with or without artificial intelligence (AI) diagnostic tool at neurological diseases diagnosis on brain CT/MRI. Routine diagnosis workflow in real clinical scenario including imaging reading, feature interpretation, differential diagnosis, writing initial report and optimizing revised version. And the gold standards of diagnosis are the histopathology references for brain tumors and the discharge diagnosis integrating all the examination results for the other neurological diseases. The performance of AI-assisted tools on diagnosing should be examined in a clinical process with multiple aspects identical to human radiologists' work before being transformed and putted to use. This study hypothesizes that AI models, trained with over 100,000 patient scans, are non-inferior to radiologists in neurological disease diagnosis on brain CT and MRI. For the secondary end-points, we investigate the performance of AI-radiologist collaboration of reasoning-enhanced AI-assisted systems. We hypothesize that, by visualizing the process of imaging interpretation and diagnosis, reasoning-enhanced AI can not only improve working performance of radiologists but also boost their trust in AI tools.
Official title: Reasoning Artificial Intelligence Collaborate With Radiologists in Neurological Disease Interpretation and Diagnosis on CT and MRI
Key Details
Gender
All
Age Range
Any - Any
Study Type
OBSERVATIONAL
Enrollment
30000
Start Date
2025-05-01
Completion Date
2030-12-01
Last Updated
2025-09-11
Healthy Volunteers
Yes
Interventions
AI-assisted diagnostic systems
Diagnosing neurological diseases on CT/MRI with and without AI-assisted tools
Locations (1)
Beijing Tiantan Hospital
Beijing, China