Artificial Intelligence in Chronic Obstructive Pulmonary Disease: Research Status, Trends, and Future Directions --A Bibliometric Analysis from 2009 to 2023

Abstract

Hupo Bian,1 Shaoqi Zhu,2 Yonghua Zhang,3 Qiang Fei,4 Xiuhua Peng,1 Zanhui Jin,1 Tianxiang Zhou,5 Hongxing Zhao1,6 1Department of Radiology, The First Affiliated Hospital of Huzhou Normal University, Huzhou, Zhejiang, People’s Republic of China; 2Department of Endocrinology, The First Affiliated Hospital of Huzhou Normal University, Huzhou, Zhejiang, People’s Republic of China; 3Department of Radiology, The Wuxing District People’s Hospital, Huzhou, Zhejiang, People’s Republic of China; 4Department of Radiology, The Linghu People’s Hospital, Huzhou, Zhejiang, People’s Republic of China; 5Department of Urinary Surgery, The First Affiliated Hospital of Huzhou Normal University, Huzhou, Zhejiang, People’s Republic of China; 6Huzhou Key Laboratory of Precise Diagnosis and Treatment of Urinary Tumors, Huzhou, Zhejiang, 313000, People’s Republic of ChinaCorrespondence: Hongxing Zhao, Department of Radiology, The First Affiliated Hospital of Huzhou Normal University, No. 158, Plaza Back Road, Wuxing District, Huzhou City, Zhejiang Province, People’s Republic of China, Email [email protected]: A bibliometric analysis was conducted using VOSviewer and CiteSpace to examine studies published between 2009 and 2023 on the utilization of artificial intelligence (AI) in chronic obstructive pulmonary disease (COPD).Methods: On March 24, 2024, a computer search was conducted on the Web of Science (WOS) core collection dataset published between January 1, 2009, and December 30, 2023, to identify literature related to the application of artificial intelligence in chronic obstructive pulmonary disease (COPD). VOSviewer was utilized for visual analysis of countries, institutions, authors, co-cited authors, and keywords. CiteSpace was employed to analyze the intermediary centrality of institutions, references, keyword outbreaks, and co-cited literature. Relevant descriptive analysis tables were created using Excel2021 software.Results: This study included a total of 646 papers from WOS. The number of papers remained small and stable from 2009 to 2017 but started increasing significantly annually since 2018. The United States had the highest number of publications among countries/regions while Silverman Edwin K and Harvard Medical School were the most prolific authors and institutions respectively. Lynch DA, Kirby M. and Vestbo J. were among the top three most cited authors overall. Scientific Reports had the largest number of publications while Radiology ranked as one of the top ten influential journals. The Genetic Epidemiology of COPD (COPDGene) Study Design was frequently cited. Through keyword clustering analysis, all keywords were categorized into four groups: epidemiological study of COPD; AI-assisted imaging diagnosis; AI-assisted diagnosis; and AI-assisted treatment and prognosis prediction in the COPD research field. Currently, hot research topics include explainable artificial intelligence framework, chest CT imaging, and lung radiomics.Conclusion: At present, AI is predominantly employed in genetic biology, early diagnosis, risk staging, efficacy evaluation, and prediction modeling of COPD. This study’s results offer novel insights and directions for future research endeavors related to COPD.Keywords: chronic obstructive pulmonary disease, artificial intelligence, visual analysis, bibliometric analysis

Keywords

• chronic obstructive pulmonary disease
• artificial intelligence
• visual analysis
• bibliometric analysis