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.
Birincil Dil | İngilizce |
---|---|
Konular | Sağlık Kurumları Yönetimi |
Bölüm | Orijinal Makale |
Yazarlar | |
Yayımlanma Tarihi | 31 Mayıs 2023 |
Yayımlandığı Sayı | Yıl 2023 |
Üniversitelerarası Kurul (ÜAK) Eşdeğerliği: Ulakbim TR Dizin'de olan dergilerde yayımlanan makale [10 PUAN] ve 1a, b, c hariç uluslararası indekslerde (1d) olan dergilerde yayımlanan makale [5 PUAN]
Dahil olduğumuz İndeksler (Dizinler) ve Platformlar sayfanın en altındadır.
Not: Dergimiz WOS indeksli değildir ve bu nedenle Q olarak sınıflandırılmamıştır.
Yüksek Öğretim Kurumu (YÖK) kriterlerine göre yağmacı/şüpheli dergiler hakkındaki kararları ile yazar aydınlatma metni ve dergi ücretlendirme politikasını tarayıcınızdan indirebilirsiniz. https://dergipark.org.tr/tr/journal/2316/file/4905/show
Dergi Dizin ve Platformları
Dizinler; ULAKBİM TR Dizin, Index Copernicus, ICI World of Journals, DOAJ, Directory of Research Journals Indexing (DRJI), General Impact Factor, ASOS Index, WorldCat (OCLC), MIAR, EuroPub, OpenAIRE, Türkiye Citation Index, Türk Medline Index, InfoBase Index, Scilit, vs.
Platformlar; Google Scholar, CrossRef (DOI), ResearchBib, Open Access, COPE, ICMJE, NCBI, ORCID, Creative Commons vs.