Automated Echocardiographic Detection of Coronary Artery Disease Using Artificial Intelligence Methods

Summary

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.

Eligibility

Inclusion Criteria:

* Patients with suspected coronary artery disease
* Patients plan to undergo coronary angiography

Exclusion Criteria:

* Patients with aortic valve stenosis
* Patients with aortic valve replacement surgery
* Patients with hypertrophic cardiomyopathy
* Patients with severe heart valve disease
* Patients with severe arrhythmia
* Patients with severe cardiomyopathy
* Patients with severe congenital heart disease
* The quality of ultrasound images is poor

Conditions2

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