Mapping intellectual structures and research hotspots in the application of artificial intelligence in cancer: A bibliometric analysis - Lyu, Peng-fei; Wang, Yu; Meng, Qing-Xiang; Fan, Ping-ming; Ma, Ke; Xiao, Sha; Cao, Xun-chen; Lin, Guang-Xun; Dong, Si-yuan (Frontiers in Oncology, 2022)
Background: Artificial intelligence（AI） is more and more widely used in cancer, which is of great help to doctors in diagnosis and treatment. The aim of this study is to summarize the current research hotspots in AACI and to qualitatively and quantitatively assess the research trends in AACI. Methods: Scientific publications for AACI-related research from 1 January 2013 to 1 April 2022 were obtained from the Web of Science database. The metrics analyses using bibliometrics software included publication, keyword, author, journal, institution, and country. The biclustering analysis on the binary matrix was performed on hot keywords. Results: The total number of papers in this study is 252. The last decade of AACI research has been divided into a slow development phase (2013-2017) and a rapid development phase (2018-2022). An international collaboration centered on the USA is dedicated to the development and application of AACI. Li J is the most prolific writer in AAIC. Through clustering analysis and high-frequency keyword research, it has been shown that AI plays a very important role in the prediction, diagnosis, treatment and prognosis of cancer. Classification, diagnosis, carcinogenesis, risk, and validation are developing topics. Eight hotspots fields of AACI were also identified. Conclusion: AACI can be of benefit to cancer patients in diagnosing cancer, assessing the effectiveness of treatment, making decision, predicting prognosis and saving costs. Future AACI research may be dedicated to optimizing AI calculation tools, improving accuracy, promotion of AI.