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Vision-Language-Based Large-Scale Model for Emergency Screening
Sponsor: The First Hospital of Jilin University
Summary
This is a single-center, prospective, stratified 1:1 parallel-group randomized superiority diagnostic trial at The First Hospital of Jilin University. Eligible emergency patients aged ≥18 who received routine thoraco-abdominal non-contrast CT were randomly assigned to two groups. The experimental group adopted a self-developed vision-language large model (powER) for auxiliary CT interpretation, while the control group received standard radiological reading without AI assistance. All participants completed standardized 60-day clinical follow-up to obtain clinical gold-standard outcomes. The primary objective is to compare the diagnostic performance of the AI model versus conventional radiology interpretation for multiple acute thoraco-abdominal emergency lesions.
Official title: Clinical Research Protocol for a Vision-Language-Based Large-Scale Model in Emergency Screening
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
INTERVENTIONAL
Enrollment
640
Start Date
2026-09-01
Completion Date
2026-11-10
Last Updated
2026-10-28
Healthy Volunteers
No
Interventions
powER vision-language large-model assisted CT reading
Standard manual interpretation of emergency thoraco-abdominal CT by radiologists with AI model assistance.
Conventional CT reading without AI assistance
Standard manual interpretation of emergency thoraco-abdominal CT by radiologists without AI model assistance.
Locations (1)
The First Hospital of Jilin University
Changchun, Jilin, China