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Cited by 6Phonocardiography and Auscultation TechniquesChronic Obstructive Pulmonary Disease (COPD) ResearchArtificial Intelligence in Healthcare

AI‐Driven Smartphone Screening for Acute COPD Exacerbations: Enhancing Health Equity in Developing Regions

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Gong, Yanbin, Xu, Chi, Mo, Caixia, Wu, Jianhui, Lin, Huiyong, Su, Huaan, Zhang, Qingpeng, Zhang, Qian +1 more·2025·npj Digital Medicine
DOI 10.1038/s41746-025-02086-zPMC PMC12638963
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Abstract

Acute exacerbations of chronic obstructive pulmonary disease (AECOPD) are critical clinical events that necessitate prompt intervention, yet their detection remains challenging in primary care, especially in resource-limited regions where a lack of awareness leads to delayed diagnoses. To address this issue, we developed an AI-based AECOPD detection system that leverages standard smartphone microphones for auscultation, specifically designed for novice users and analyzing sounds to screen for AECOPD without requiring subjective patient-reported scales. Our system demonstrated robust performance, achieving an area under the curve (AUC) of 0.955 (95% CI: 0.929-0.976). A state-transition health-economic model projected per-capita net savings of 456.9 CNY (95% CI: -88.2 to 1,779.3) with a 90.3% probability of positive returns, supporting cost-effective implementation. This research highlights the potential of AI-driven solutions to enhance COPD management in underserved populations, providing a scalable tool to promote health equity where access to pulmonary specialists is constrained.

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Cited by

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Authors
Gong, Y., Xu, C., Mo, C., Wu, J., Lin, H., Su, H., Zhang, Q., Zhang, Q., & Yang, S.
Affiliations
  • Hong Kong University of Science and Technology (HK)
  • Guangdong Academy of Medical Sciences (CN)
Corresponding author
  • Zhang, Qingpeng
  • Zhang, Qian
  • Yang, Shifang
ORCID
Venue
npj Digital Medicine
Publisher
Springer Science and Business Media LLC
Published
2025-11-21
Volume
8
Issue
1
Pages
715-715
ISSN
2398-6352 (ISSN-L)
DOI
10.1038/s41746-025-02086-z
PMC
PMC12638963
OpenAlex
W4416470773
Cited by
6
References
2
Citations by year
2026: 6
FWCI
3.94
Type
journal article
Language
en
Open access
Licence
Locations
  • npj Digital Medicine (publishedVersion, cc-by-nc-nd)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Rare & Special e-Zone (The Hong Kong University of Science and Technology) (submittedVersion)
Funders
Hong Kong RGC (HB016, 16206122)
Topics
  • Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Phonocardiography and Auscultation Techniques
  • Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Chronic Obstructive Pulmonary Disease (COPD) Research
  • Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
Keywords
COPD exacerbations, chronic obstructive pulmonary disease, lung sound analysis, primary care screening, resource-limited settings, health equity, cost-effectiveness, state transition model, delayed diagnosis

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