Chronic obstructive pulmonary disease (COPD) is a global healthcare challenge. It is highly prevalent in low-income countries, causes 3 million death per year and is projected to be the leading cause of death globally by 2030. Challenges in COPD management result in care quality gaps which impair timely and accurate diagnosis and limit patient stratification and provision of evidence-based interventions. COPD exacerbations are responsible for a large proportion of the disease-burden, adverse outcomes and healthcare costs. There is a requirement to re-orientate COPD exacerbation care from failure-driven reactive approach to one based on proactive preventative management. Service model adaptation supported by artificial intelligence (AI) tools offer the prospect of addressing these care-quality gaps and achieving this practice re-orientation. Progress with clinical applications of AI for COPD is accelerating. Evidence available demonstrates the potential of AI techniques to facilitate early and precise COPD case-finding and diagnosis, allow stratification with clinical decision support to prioritise management, and achieve accurate exacerbation detection/prediction to allow proactive interventions. In this narrative review, we will summarise current evidence for the application of AI to these COPD challenges, outline the barriers to implementation of AI models and present our opinion on the required next steps to realise the potential role for AI in COPD management.
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