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Heart Sound Analysis Using Machine Learning in patients with Aortic Valve Stenosis

Heart Sound Analysis Using Machine Learning in patients with Aortic Valve Stenosis - Heart Sound Analysis Using Machine Learning in patients with Aortic Valve Stenosis

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
JPRN
Registry ID
JPRN-UMIN000046448
Enrollment
1100
Registered
2021-12-24
Start date
2021-09-14
Completion date
Unknown
Last updated
2026-06-29

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Aortic stenosis

Interventions

None listed

Sponsors

Department of Cardiovascular Medicine, Faculty of Medicine and Graduate School of Medicine, Hokkaido University
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: <AS group> (1) Those who are 20 years old or older at the time of obtaining consent (2) Those who have been diagnosed with aortic valve stenosis 3) Those who will undergo echocardiography. (3) Those who do not refuse to participate in this study. <Non-AS group> 1) Those who are 20 years old or older at the time of obtaining consent. (2) Patients who have a systolic murmur, but aortic stenosis has been ruled out. (3) Patients who do not refuse to participate in this study. <Control group> (1) Patients aged 20 years or older at the time of obtaining consent (2) Those who do not have a systolic murmur (3) Patients who will undergo echocardiography 3) Those who do not refuse to participate in this study.

Exclusion criteria

Exclusion criteria: <Common to all three groups> (1) Those who refuse to cooperate in the research after disclosing the information using the opt-out method. (2) Others who are judged by the principal investigator to be inappropriate as research subjects.

Design outcomes

Primary

MeasureTime frame
Relationship between the severity of AS estimated by deep learning and the severity of AS estimated by the Japanese Circulation Society Guidelines for the Treatment of Valvular Heart Disease, revised in 2020.

Countries

Japan

Contacts

Public ContactYoshifumi Miziguchi

Faculty of Medicine and Graduate School of Medicine, Hokkaido University Department of Cardiovascular Medicine

mizu-tay@med.hokudai.ac.jp011-706-6973

Outcome results

None listed

Source: JPRN (via WHO ICTRP) · Data processed: Jul 3, 2026