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AI-Powered Sound Analysis for COPD Screening

NCT07457073 · Status: ACTIVE_NOT_RECRUITING · Type: OBSERVATIONAL · Enrollment: 3000

Last updated 2026-03-25

No results posted yet for this study

Summary

Chronic Obstructive Pulmonary Disease (COPD) is a leading cause of morbidity and mortality worldwide, yet early detection remains challenging-especially in primary care settings where spirometry, the diagnostic gold standard, is often unavailable. This study aims to develop and validate a non-invasive, low-cost COPD screening tool based on artificial intelligence (AI) analysis of cough sounds. Using smartphone-recorded cough audio and clinical data from both COPD patients and non-COPD controls, the investigators will train and test an AI model to identify acoustic signatures associated with COPD. The model will be developed using a prospective cohort from Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, and externally validated in a community-based cohort across nine districts/counties in Zhejiang Province, China.

Conditions

  • Chronic Obstructive Pulmonary Disease (COPD)

Sponsors & Collaborators

  • Sir Run Run Shaw Hospital

    lead OTHER

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2026-02-23
Primary Completion
2027-02-01
Completion
2027-06-01

Countries

  • China

Study Locations

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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 NCT07457073 on ClinicalTrials.gov