Global evolution of research on pulmonary nodules: a bibliometric analysis

Author:

Li Ning1ORCID,Wang Lei1,Hu Yaoda1,Han Wei1,Zheng Fuling2,Song Wei2,Jiang Jingmei1

Affiliation:

1. Department of Epidemiology & Biostatistics, Institute of Basic Medicine Sciences, Chinese Academy of Medical Sciences/School of Basic Medicine, Peking Union Medical College, Beijing, 100005, China

2. Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, 100730, China

Abstract

Aim: To provide a historical and global picture of research concerning lung nodules, compare the contributions of major countries and explore research trends over the past 10 years. Methods: A bibliometric analysis of publications from Scopus (1970–2020) and Web of Science (2011–2020). Results: Publications about pulmonary nodules showed an enormous growth trend from 1970 to 2020. There is a high level of collaboration among the 20 most productive countries and regions, with the USA located at the center of the collaboration network. The keywords ‘deep learning’, ‘artificial intelligence’ and ‘machine learning’ are current hotspots. Conclusions: Abundant research has focused on pulmonary nodules. Deep learning is emerging as a promising tool for lung cancer diagnosis and management.

Funder

Peking Union Medical College Innovation Fund for Graduate Student

Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences

Publisher

Future Medicine Ltd

Subject

Cancer Research,Oncology,General Medicine

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