Breathing life into data: A critical review of artificial intelligence and computational modelling in COPD precision management.

The escalating global burden of chronic obstructive pulmonary disease (COPD) has outpaced the capacity of conventional management paradigms to deliver truly individualized care. This review offers a critical, narrative synthesis of the role of artificial intelligence and computational modelling in advancing COPD precision management, integrating technical, clinical, and policy evidence streams that have largely been treated separately in prior surveys. Reporting follows the spirit of the PRISMA-ScR checklist, and the search strategy is fully described to permit replication. The scope is cross-modal and explicitly regional, spanning pathophysiological understanding, diagnostic and prognostic applications, personalized treatment regimen optimization, exacerbation prediction, and drug discovery and repurposing. Key computational approaches-including mechanistic, multiscale, and machine learning models-are appraised for their contributions to disease phenotyping and prediction. The review critically examines persistent challenges, including data availability and quality, model interpretability and explainability, ethical considerations and algorithmic bias, and barriers to clinical integration. Future directions encompass multimodal data integration, explainable AI development, and rigorous clinical validation and implementation. By consolidating evidence across disciplines, this review maps current capabilities, exposes critical gaps, and outlines strategic priorities for translating computational innovation into tangible improvements in COPD diagnosis, treatment, and patient outcomes.