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Artificial Intelligence in Detecting Cardiac Function

NCT06444425 · Status: ENROLLING_BY_INVITATION · Type: OBSERVATIONAL · Enrollment: 685

Last updated 2025-02-17

No results posted yet for this study

Summary

The Korotkoff Sounds（KS）, which have been in use for over a century, are widely regarded as the gold standard for measuring blood pressure. Furthermore, their potential extends beyond diagnosis and treatment of cardiovascular disease; however, research on the KS remains limited. Given the increasing incidence of heart failure (HF), there is a pressing need for a rapid and convenient prehospital screening method. In this study, we propose employing deep learning (DL) techniques to explore the feasibility of utilizing KS methodology in predicting functional changes in cardiac ejection fraction (LVEF) as an indicator of cardiac dysfunction.

Conditions

Sponsors & Collaborators

  • Zhejiang Taizhou hospital

    collaborator UNKNOWN

  • The People's Hospital of Quzhou

    collaborator OTHER

  • Zhejiang Quhua Hospital

    collaborator OTHER

  • Hong Kong Applied Science and Technology Research Institute

    collaborator UNKNOWN

  • The Fourth Affiliated Hospital of Zhejiang University School of Medicine

    lead OTHER

Principal Investigators

  • Sixiang Jia, MD · The fourth hospital affiliated to zhejiang university school of medicine

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2024-06-01
Primary Completion
2024-12-31
Completion
2025-12-31

Countries

  • China

Study Locations

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Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06444425 on ClinicalTrials.gov