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Automated Echocardiographic Detection of Coronary Artery Disease Using Artificial Intelligence Methods

StatusRecruiting
PhaseNot specified
Started
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Record status
This record was last updated November 21, 2025 (before its estimated March 11, 2026 completion). Its status may not reflect the trial's current state.

Record History

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  1. Trial status: Not Yet Recruiting to Recruiting
    • Study completion date: Apr 11, 2026 to May 11, 2026
    • Eligibility criteria expanded, about 15 words
    v2
  2. Study First Submitted
  • Stopped: an ongoing trial was terminated, suspended or withdrawn.
  • Notable: the trial’s plan changed such as a big move in its timeline or size, a new primary endpoint, sponsor or phase, or recruiting opened or resumed.
  • Minor: routine progress and housekeeping, such as sites added or enrollment closed.
The incidence rate and mortality of coronary artery disease are increasing year by year. Exploring non-invasive, accurate, and widely applicable methods to screen and diagnosis is of great significance. New ultrasound techniques, such as non-invasive myocardial work, have been proven to be superior to traditional ultrasound techniques in screening and diagnosis. However, diagnostic analysis based on ultrasound video images is time-consuming and subjective. The progress of artificial intelligence technology in fully automated quantitative evaluation of video images provides the possibility for computer-aided design screening and diagnosis. At present, the application of artificial intelligence in computer-aided design is a cutting-edge issue in the field of cardiovascular disease research. The application of artificial intelligence technology in the construction of computer-aided diagnostic models based on ultrasound video images is still in its early stages.
Trial Details
NCT Number NCT06314295
Lead Sponsor Beijing Hospital
Conditions
(from sponsor)		 Coronary Artery Disease
Related terms Coronary Artery Disease
Enrollment 1,500 participants
Start Date
Primary Completion (estimated)
Study Completion (estimated)
Updated on ClinicalTrials.gov