This project aims to collaborate with multiple medical institutions to verify the accuracy, stability, and clinical application value of AI algorithms in echocardiographic quantitative measurement through multi-center clinical research. Specific objectives include:
1. Compare the automatic measurement results of AI with the manual measurement data from physicians of different levels, and analyze the measurement deviation and consistency of AI in key parameters such as intracardiac diameter, volume, and function. 2. Investigate whether AI-assisted measurement can significantly reduce echocardiogram analysis time and optimize clinical workflows. Through multi-center data validation, establish a standardized reference system for AI ultrasound measurement, promote the promotion and application of AI technology in medical institutions at all levels, and reduce diagnostic differences between different hospitals and physicians. 3. Exploring the application of AI in special cases: Assessing the measurement stability of AI algorithms in complex cases (such as cardiomyopathy, valvular disease, coronary heart disease, etc.), and optimizing AI models to meet broader clinical needs.
Age ≥18 - 80 years;
Normal heart
Coronary heart disease (with segmental thinning and abnormal movement)
Valve disease (valve stenosis or reflux)
Patients with congenital heart disease
Patients with poor image quality