Actively Recruiting
Artificial Intelligence in Aortic Regurgitation
Led by Chinese University of Hong Kong · Updated on 2026-03-20
540
Participants Needed
1
Research Sites
121 weeks
Total Duration
On this page
Sponsors
C
Chinese University of Hong Kong
Lead Sponsor
S
Semmelweis University
Collaborating Sponsor
AI-Summary
What this Trial Is About
This research project aims to develop and validate a tool that uses artificial intelligence (AI) to automatically detect and quantify aortic regurgitation (AR). The clinical efficacy of this tool will be established by comparing it to manual diagnostic methods in a multicenter randomized controlled trial. By leveraging deep learning (DL) techniques, the AI system will automate aortic regurgitation (AR) detection, measurement, and diagnosis, addressing challenges like variability in echocardiographic interpretations and the need for specialized expertise. It will integrate multiple echocardiographic parameters to provide accurate, standardized, and efficient AR diagnoses, reducing human error and improving consistency. This tool will enhance diagnostic precision and accessibility, improving clinical outcomes and extending advanced diagnostic capabilities to a broader range of healthcare environments, including resource-limited settings.
CONDITIONS
Official Title
Artificial Intelligence in Aortic Regurgitation
Who Can Participate
Eligibility Criteria
You may qualify if you...
- Confirmed AR diagnosis via TTE and Doppler imaging per guidelines.
- Age �318 years.
- Adequate acoustic window for AR quantification.
You will not qualify if you...
- Prior cardiac transplant or implanted cardiac devices.
- Poor image quality.
- Pregnancy or lactation.
AI-Screening
AI-Powered Screening
Complete this quick 3-step screening to check your eligibility
Trial Site Locations
Total: 1 location
1
Division of Cardiology, Department of Medicine and Therapeutics Faculty of Medicine, The Chinese University of Hong Kong
Hong Kong, New Territories, Hong Kong, Sha Tin
Actively Recruiting
Research Team
X
Xueting Wang
CONTACT
How is the study designed?
Study Type
INTERVENTIONAL
Masking
DOUBLE
Allocation
RANDOMIZED
Model
PARALLEL
Primary Purpose
DIAGNOSTIC
Number of Arms
2
Not the Right Trial for You?
Explore thousands of other clinical trials that might be a better match.
Sign up to get personalized trial recommendations delivered to your inbox.
Already have an account? Log in here