Background: Interest in bronchiectasis is increasing and no prior study has used artificial intelligence (AI) to interrogate its rich, multidimensional literature to characterise research trends, themes and knowledge gaps.
Methods: We reviewed original bronchiectasis research between 1949 and 2024 (a 75-year period) to identify, characterise and assess research trends and trajectories using two AI-powered approaches: 1) Atlas, an AI topic-modelling tool; and 2) a custom model, leveraging ChatGPT embedding and text generation models.
Results: AI-powered analytics revealed a nine-fold increase in bronchiectasis research speed since 2000, typified by enhanced richness with four new research topics emerging every 5 years. Publication trends mirror clinical and technological advances, exemplified by significant rises in computed tomography, microbiome and clinical studies following the adoption of high-resolution computed tomography (1970s), next-generation sequencing (2005) and the first clinical guidelines (2008-2010), respectively. Topics with sustained growth (i.e. popular topics) include bronchiectasis-COPD overlap, microbiome infection, cardiovascular health and exacerbations. Those with sudden, short-term increased interest (i.e. trending topics) have focused on microbial pathogens and primary ciliary dyskinesia genetics. Mortality represents a nascent topic, demonstrating the highest year-on-year interest. Growth of research within the "vicious vortex" demonstrates thematic imbalance, with few studies overlapping with non-vortex components. Evolving research focus towards inflammation is evident, with increased work on comorbidities and quality of life demonstrating a shift from disease-centric to patient-centric research.
Conclusion: AI captures bronchiectasis as a dynamic and interdisciplinary field in continuing growth. Emerging research topics extend beyond the vicious vortex framework, indicating a transition from disease-centric to patient-centric approaches to optimise clinical care.
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