AI-Powered Sound Analysis for COPD Screening

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.

NCT Number	NCT07457073
Lead Sponsor	Sir Run Run Shaw Hospital
Conditions	Chronic Obstructive Pulmonary Disease (COPD)
Enrollment	3,000 participants
Start Date	2026-02-23
Primary Completion	2027-02-01 (estimated)
Study Completion	2027-06-01 (estimated)
Updated on ClinicalTrials.gov	2026-03-25