Artículo

Bibliometric analysis of the application of deep learning in cancer from 2015 to 2023

Resumen

Background Recently, the application of deep learning (DL) has made great progress in various fields, especially in cancer research. However, to date, the bibliometric analysis of the application of DL in cancer is scarce. Therefore, this study aimed to explore the research status and hotspots of the application of DL in cancer. Methods We retrieved all articles on the application of DL in cancer from the Web of Science database Core Collection database. Biblioshiny, VOSviewer and CiteSpace were used to perform the bibliometric analysis through analyzing the numbers, citations, countries, institutions, authors, journals, references, and keywords. Results We found 6,016 original articles on the application of DL in cancer. The number of annual publications and total citations were uptrend in general. China published the greatest number of articles, USA had the highest total citations, and Saudi Arabia had the highest centrality. Chinese Academy of Sciences was the most productive institution. Tian, Jie published the greatest number of articles, while He Kaiming was the most co-cited author. IEEE Access was the most popular journal. The analysis of references and keywords showed that DL was mainly used for the prediction, detection, classification and diagnosis of breast cancer, lung cancer, and skin cancer. Conclusions Overall, the number of articles on the application of DL in cancer is gradually increasing. In the future, further expanding and improving the application scope and accuracy of DL applications, and integrating DL with protein prediction, genomics and cancer research may be the research trends.
Wang, Ruiyu (58237487600); Huang, Shu (59151617000); Wang, Ping (59204984800); Shi, Xiaomin (55334817900); Li, Shiqi (58958529700); Ye, Yusong (58803264300); Zhang, Wei (59151288700); Shi, Lei (57189389986); Zhou, Xian (55550465400); Tang, Xiaowei (56446021000)
Bibliometric analysis of the application of deep learning in cancer from 2015 to 2023
2024
10.1186/s40644-024-00737-0
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85197545856&doi=10.1186%2fs40644-024-00737-0&partnerID=40&md5=83de0ee897b281e9e2d813e3abaea5be
Department of Gastroenterology, The Affiliated Hospital of Southwest Medical University, Street Taiping No.25, Region Jiangyang, Sichuan Province, Luzhou, 646099, China; Nuclear Medicine and Molecular Imaging Key Laboratory of Sichuan Province, Luzhou, China; Department of Gastroenterology, Lianshui County People’ Hospital, Huaian, China; Department of Gastroenterology, Lianshui People’ Hospital of Kangda CollegeAffiliated to, Nanjing Medical University, Huaian, China
All Open Access; Gold Open Access
Scopus
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