Current trends and future artificial intelligence applications in transfusion medicine: a bibliometric analysis

Abstract

BACKGROUND: Artificial Intelligence (AI) is increasingly vital in transfusion medicine for enhancing service quality and efficiency. However, bibliometric studies in this area are scarce. This analysis maps current and emerging research trends. RESEARCH DESIGN AND METHODS: Publications from 1 January 2000 to 31 August 2025, were retrieved from the Web of Science Core Collection. VOSviewer, CiteSpace, and Excel were used to visualize contributions and trends across authors, institutions, journals, and countries. RESULTS: Among 159 publications, the U.S.A. China, and India led in output. The University of Colorado was the top institution, while Transfusion had the highest citations. Axel Hofmann was the most cited author. Keywords such as 'machine learning' and 'deep learning' highlight the rapid adoption of advanced AI technologies. CONCLUSIONS: This study outlines current trends and emerging frontiers, offering valuable insights and guidance for future AI applications in transfusion medicine.

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