AI Assisted Screening for VHD Using Routine Chest CT Scans
Condition(s) studied
Study summary
This is a prospective, multicenter study designed to validate a deep learning model for screening valvular heart diseases using routine, non-contrast chest computed tomography (CT) scans.
The primary objective is to evaluate the model's diagnostic performance, with the sensitivity serving as the primary efficacy endpoint. Secondary endpoints will include other performance metrics such as area under the receiver operating characteristic curve (AUC), specificity, and accuracy, etc.
Eligibility
Primary outcome measure(s)
- Sensitivity — 1 year
Sensitivity: Measures the proportion of patients with moderate-to-severe disease that the model correctly identifies.
Trial sites (3)
| Facility | City | Region | Status |
|---|---|---|---|
| Renmin Hospital of Wuhan University | Wuhan | Hubei | Recruiting |
| Xinjiang Uygur Autonomous Region People's Hospital | Ürümqi | Xinjiang | Recruiting |
| The Second Affiliated Hospital of Zhejiang University School of Medicine | Hangzhou | Zhejiang | Recruiting |
More Second Affiliated Hospital, Zhejiang University, School of Medicine trials in China
Other trials for the same condition
This page summarises publicly available registry data for informational purposes — not medical advice. Eligibility is determined by each study team; patients should discuss participation with their clinician.
View NCT07449130 on ClinicalTrials.gov ↗ ← All trials in China