关键词: 3D生物打印技术, 文献计量, 数据挖掘, 发展态势, 可视化分析

Abstract: This article uses the Web of Science core collection database as the statistical source, carries on the bibliometric analysis of the 3D bioprinting technology articles included in the database, and uses Derwent Data Analyzer (DDA) and VOS viewer visualization software to compare the development trend of global 3D bioprinting technology. The Web of Science core collection database contains 15,736 articles in the research field of 3D bioprinting technology, and the amount of publications is generally increasing year by year. Research hotspots are concentrated in the direction of scaffolds and tissue engineering. Since 2015, the number of articles published on 3D bioprinting technology has increased significantly. The United States has the largest number of papers, and China ranks second. The institutions with the largest number of published papers are the University of California System in the United States, Shanghai Jiaotong University as the most prolific institution in China, and Hutmacher Dietmar W of The Queensland University of Technology is the most prolific author. With many universities and top talents with strong scientific research strength, the United States is at the center of the global 3D bioprinting research cooperation network and occupies an important position in the global research cooperation network. The research and development of 3D bioprinting technology in China is fast, and occupies the international leading level. However, there is still a gap in terms of China’s academic influence compared to the international top level. Research in stereolithography, computer-aided design, etc., needs to be strengthened. Therefore, China still needs to strengthen major basic and cutting-edge scientific research, continuously deepen international exchanges and cooperation, attract a number of international top scientific and technological talents, and promote the development of 3D bioprinting technology and industry.

Key words: 3D Bioprinting Technology, Bibliometrics, Data Mining, Development Trend, Visual Analysis