全膝关节置换术后血栓形成的数据挖掘及聚类分析

目的：探讨全膝关节置换术与血栓形成之间的研究热点,及其年度趋势与活跃期刊的分布。方法：使用PubMed检索文献、BICOMB数据挖掘、gCLUTO聚类分析,并基于主要主题词的共词矩阵建立战略坐标。结果：相关的289种期刊的1 039篇文献中,最活跃的20种期刊共发表522篇文献,所占比例为50.24%。通过对28个高频主题词的双聚类及绘制战略坐标,发现4类研究热点,其中类别2“全膝关节置换术中静脉血栓等术后并发症的防控方法”可成为未来研究的热点之一。结论：“全膝关节置换术中静脉血栓等术后并发症的防控方法”是临床上面临的重要问题,但目前血栓这一并发症的发生仍无法预测,人工智能应用于医学或许能够解决这个问题。

Data mining and cluster analysis of thrombosis after total knee arthroplasty

Objective To study the research hotspots in total knee arthroplasty and thrombosis and the distribution of their annual trend and active journals. Methods The papers on total knee arthroplasty and thrombosis were retrieved from PubMed, the data of total knee arthroplasty and thrombosis were mined with BICOMB and analyzed by cluster analysis with gCLUTO, and the strategic coordinate of data of total knee arthroplasty and thrombosis was plotted according to the co-words matrix of the main subject headings. Results Of the 1039 papers published in 289 journals, 522 (50.24%) were published in the 20 most active journals. The double clustering of 28 high frequency subject headings and the strategic coordinate for the data of total knee arthroplasty and thrombosis showed 4 types of research hotspots, and type 2 "prevention and control of complications such as venous thrombosis after total knee arthroplasty" might become one of the future research hotspots. Conclusion Prevention and control of complications such as venous thrombosis after total knee arthroplasty are an important problem in clinical practice, but the occurrence of thrombosis can not be predicted at present, which can be solved when artificial intelligence is applied in medical field.