Research hotspots and trends of artificial intelligence in lymphoma: A bibliometric analysis from 2010 to 2024

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Background At present, artificial intelligence (AI) plays a significant role in the diagnosis, treatment, and prognosis of lymphoma. This study quantitatively analyzed the research hotspots and future trends in this field by using bibliometric software. The aim is to offer researchers a full understanding of the current research along with suggestions for future directions. Methods All relevant articles of AI in lymphoma research were retrieved from the Web of Science Core Collection database from 2010 to 2024. Bibliometric visualization analysis of all retrieved data was conducted by using the “ bibliometrix ” package in R (version 4.4.1), CiteSpace (version 6.4.R1), and VOSviewer (version 1.6.20). Results Analysis of 662 publications shows that AI in lymphoma research is currently on rapid development. The United States and China are ahead of other countries in terms of the number of articles and citations. Jiang Huiyan from Northeastern University (China) and Michel Meignan from Assistance Publique-Hôpitaux de Paris (France) are the most prolific and highly cited authors in this field. Recent hotspots focus on molecular expression and imaging histology, while the emerging directions are molecular mechanisms and chemotherapeutic strategies in lymphoma. Conclusions This study comprehensively analyzes the hotspots and trends of AI research in lymphoma, which is shifting from radiomics toward molecular mechanisms and AI-optimized chemotherapy. In the future, it is necessary to meet the practical clinical demands and promote the integration of AI.