Bibliometric analysis of the 50 most cited articles on artificial intelligence for lung cancer imaging

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 most influential publications on artificial intelligence (AI) for cancer.
 Material and Method: A comprehensive PubMed SCImago Journal Country Rank (SJR) search was performed. 50 cited articles were recorded according citation numbers, country institute articles, name metrics publishing journal, year publication, content articles. 
 Results: numbers ranged from 24 628. Annual citations per article between 1.47 104.6. USA with (n=22) followed by Netherlands (n=9) Peoples R China (n=5). journal institution that highly contributed Radiology (n=5) Harvard Medical School (n=5), respectively.
 Conclusion: importance deep AI cancer imaging increasing day day. In this study, a detailed bibliometric analysis literature addition, informs researchers about current papers field, characteristics these studies, potential future trends rapidly evolving field screening.