Detection of Valvular Heart Disease Using Artificial Intelligence-based Stethoscope

Xiao-dong Zhuang2,000 enrolled

Overview

The aim of this study is to develop a deep learning-based application of heart sounds in the diagnosis of valvular heart disease, which can be used to screen patients with valvular heart disease and promote earlier clinical monitoring and intervention.

Study Type

OBSERVATIONAL

Enrollment

2,000

Conditions

Valvular Heart Disease

Interventions

artificial intelligence-based stethoscopeOTHER

artificial intelligence-based stethoscope

Eligibility

Sex: ALLMin age: 18 YearsMax age: 100 Years

Medical Language ↔ Plain English

Inclusion Criteria: 1. age\>18 years 2. In the past 1 month, echocardiography was performed to diagnose valvular heart disease (positive group) and echocardiography to exclude valvular heart disease (negative group). 3. Consent to study and be able to sign informed consent Exclusion Criteria: 1. After prosthetic valve replacement 2. Congenital heart disease (except bilobal aortic valve) 3. Hypertrophic Cardiomyopathy（HCM） 4. Pregnant, lactating women

Locations (1)

First Affiliated Hospital, Sun Yat-Sen University

Guangzhou, Guangdong, China

RECRUITING

Outcomes

Primary Outcomes

valvular heart disease

Reports therefore graded VHD as none, mild, moderate, severe, or critical, with additional borderline categories (eg, moderate to severe) also allowed

Time frame: 10 months

Data from ClinicalTrials.gov

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