AI-driven smartphone screening for acute COPD exacerbations: enhancing health equity in developing regions.

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

SUBMITTER: Gong Y 

PROVIDER: S-EPMC12638963 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature