Abstract
Aim: The use of machine learning has now become widespread in lung cancer. However, the research trend is still unclear. This study aimed to analyze the most influential publications on artificial intelligence (AI) for lung cancer.
 Material and Method: A comprehensive PubMed and SCImago Journal and Country Rank (SJR) search was performed. The 50 most cited articles were recorded according to the citation numbers, the country and institute of articles, the name and metrics of the publishing journal, the year of publication, and the content of the articles. 
 Results: The citation numbers ranged from 24 to 628. Annual citations per article was between 1.47 and 104.6. The USA was the country with the most publications (n=22) followed by The Netherlands (n=9) and Peoples R China (n=5). The journal and institution that highly contributed to the 50 most cited articles were Radiology (n=5) and Harvard Medical School (n=5), respectively.
 Conclusion: The importance of deep learning and AI in lung cancer imaging is increasing day by day. In this study, a detailed bibliometric analysis of the literature on AI in lung cancer imaging was performed. In addition, this bibliometric analysis informs researchers about current influential papers in this field, the characteristics of these studies, and potential future trends in the rapidly evolving field of AI in lung cancer screening.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
