Application of artificial intelligence in glioma researches: A bibliometric analysis

Abstract

Background: There have been no researches assessing the research trends of the application of artificial intelligence in glioma researches with bibliometric methods. Purpose: The aim of the study is to assess the research trends of the application of artificial intelligence in glioma researches with bibliometric analysis. Methods: Documents were retrieved from web of science between 1996 and 2022. The bibliometrix package from Rstudio was applied for data analysis and plotting. Results: A total of 1081 documents were retrieved from web of science between 1996 and 2022. The annual growth rate was 30.47%. The top 5 most productive countries were the USA, China, Germany, France, and UK. The USA and China have the strongest international cooperative link. Machine learning, deep learning, radiomics, and radiogenomics have been the key words and trend topics. "Neuro-Oncology", "Frontiers in Oncology", and "Cancers" have been the top 3 most relevant journals. The top 3 most relevant institutions were University of Pennsylvania, Capital Medical University, and Fudan University. Conclusions: With the growth of publications concerning the application of artificial intelligence in glioma researches, bibliometric analysis help researchers to get access to the international academic collaborations and trend topics in the research field.

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Stored only when both papers are in the corpus — 17 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.