关键词: 风险预测模型, CiteSpace, 文献计量学, 医药领域

Abstract: Objective To understand the research hotspots and trend analyses of risk prediction models in China's pharmaceutical field,and to provide reference for subsequent research. Methods Using China National Knowledge Infrastructure（CNKI）,Wanfang Data and Wipro Chinese Journal Service Platform as data sources,this study searched for relevant literature collected from the establishment of the database to January 2024,and used Noteexpress and CiteSpace software to visualise and analyse the number of publications,authors,research institutes and keywords of the collected literature. Results A total of 2 694 articles were retrieved that met the requirements,and the number of literature issuances showed a rising trend year by year,especially after 2019,which increased abruptly. Core authors within the field hadnot been formed,and there was a lack of cooperation and communication between different institutions. The analysis yielded 13 high-frequency keywords,10 clusters,and 9 strongest mutated words. The hot topics of research included predictive model construction,risk factor analysis,and the elderly,and the research trends were risk assessment,ovarian cancer,breast cancer,and so on. Conclusion Risk prediction models are valued and used by pharmaceutical practitioners to construct appropriate models to solve complex clinical problems,but knowledge and understanding of risk prediction models still need to be enhanced.

Key words: Risk prediction model, CiteSpace, Bibliometry, Pharmaceutical field