ReviewLasers in medical science2025
Global trends and hotspots in AI applications for CT detection of chronic obstructive pulmonary disease: A bibliometric analysis from 2012 to 2024.
Review in Lasers in medical science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeChronic obstructive pulmonary disease (COPD) is a progressive inflammatory lung disease that significantly impacts global health. This study aims to comprehensively analyze global trends and research hotspots in the application of artificial intelligence (AI) for computed tomography (CT) detection of COPD.
methodsPublications related to AI applications for CT detection in COPD from 2012 to 2024 were retrieved from the Web of Science Core Collection (WoSCC) database. Bibliometric analysis was conducted using VOSviewer, CiteSpace, and the R package "bibliometrix".
resultThe field has experienced publications growth, with 189 publications and an annual growth rate of 37.83%. The United States led with 53 publications, followed by China (51) and Germany (13). The University of Iowa was the most prolific institution (69), followed by Harvard University (47) and Brigham and Women's Hospital (37). Hoffman Eric A. is the most prolific author with 16 publications, and journals such as Scientific Reports and Radiology were key contributors to the field. Emerging topics included "quantitative imaging", "low dose CT", "pulmonary disease", "body mass index", "subpopulations", and "prevalence", suggested growing interest in comprehensive patient assessment and population studies.
conclusionThis bibliometric analysis provides a comprehensive overview of research on AI applications for CT detection of COPD from 2012 to 2024, identifying key contributors, research hotspots, and emerging trends. Future research should focus on differentiating COPD from other lung diseases or COPD subpopulations for personalized treatment. CLINICAL TRIAL NUMBER: not applicable.
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Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.