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Artificial intelligence in immune checkpoint inhibitor research: A bibliometric analysis of the landscape
Jian Kang1,2, Rui Tang2, Dongqi Li2
1Department of Urology, Second Affiliated Hospital of Anhui Medical University, Hefei, China.
Abstract:
This bibliometric analysis examines the transformative role of artificial intelligence (AI) in immune checkpoint inhibitor (ICI) research. Using VOSviewer, CiteSpace, and Bibliometrix, we analyzed 1,938 publications from the Web of Science Core Collection (2015-2026), revealing a dramatic rise in AI-related ICI studies, led by China and the USA. Key findings demonstrate AI's integration in predicting treatment response, optimizing dosing strategies, and managing immune-related adverse events. Through keyword co-occurrence and citation analyses, we identify critical AI applications including digital pathology and tumor microenvironment characterization. This comprehensive overview provides valuable insights into research trends and emerging frontiers for AI-driven innovations in cancer immunotherapy.
