基于机器学习算法的压力性损伤风险预测研究热点的可视化分析

A visual analysis of research hotspots for pressure injury risk prediction based on machine learning algorithms

目的:应用文献计量学方法分析基于机器学习算法的压力性损伤风险预测的研究热点和发展趋势。方法:检索中国知网、万方、维普和PubMed数据库自建库至2022年10月31日收录的相关文献,运用书目共现分析系统软件提取文献数据,运用CiteSpace和gCLUTO对文献数据进行可视化聚类分析。结果:共检索到1504篇文献,其中中文文献共1239篇,英文文献265篇。按照纳入、排除标准筛选后共纳入89篇文献,包括中文文献38篇(42.70%)、英文文献51篇(57.30%)。该领域中英文文献发文量整体呈增长趋势。纳入的文献发表于63种期刊,其中中文期刊25种,英文期刊38种。纳入文献的合著率为91.01%。有基金支持的文献共45篇(50.56%)。研究主要涉及的人群包括ICU患者、手术患者以及老年患者。中文文献共提取98个主题词,英文文献共提取主题词59个。中文文献的研究热点分为4组:Braden评分、预测、压力性损伤、预测模型。英文文献的研究热点分为4组:ICU(重症监护病房)、Pressure ulcers(压力性损伤)、nomogrand(列线图)and machine learning(机器学习)。结论:基于机器学习算法的压力性损伤风险预测研究尚处于发展阶段,今后研究应强化预测模型研究设计的科学性和完整性,未来可以开展不同专科压力性损伤风险预测模型的构建及验证研究、机器学习算法的培训及护理教育研究。

Objective:To analyze the research hotspots and development trends of pressure injury risk prediction based on machine learning algorihms by using bibliometric methods.Methods:CNKI,Wanfang,VIP and PubM ed databases were retrieved from the inception of databases to October 31,2022.The bibliographic cor occurrence analysis system software was used to extract the literature data.CiteSpace and gCLUTO software were used to visually cluster the lieraure dala.Results:A total of 1504 articles were retrieved,including 1239 Chinese articles and 265 English articles.According to the inclusion and exclusion crteria,89 artides w ere included,induding 38 Chinese aricles(42.70%)and 51 English articles(5730%),The number of papers published in Chinese and English in this field showed an overall incrcasing trend.The included articles were published in 63 joumals,including 25 Chinese joumals and 38 English journals.The co-author rale of the induded literature was 91.01%There were 45 articles with fund support(50.56%).The study mainly involved ICU patients,surgical patients and elderly patients.A total of 98 keywords were extracted from Chinese literalure and 59 key words were extnacted from English literalture.The research hotspots of Chinese litenature were divided into four groups ineluding Braden score,prediction,pressure injury and prediction model.The research holspots of English literalure were divided into four groups including intensive care unil,pressure ulcers,nomogram and machine learning.Conclusion:The researches on the risk prediction of pressure injury based on machine leaming algorithm is still in the developmental stage In the future,the sci-entific and integnity of the research and design of the prediction model should be strenghened.The fllowing can also be used as future research directions such as the construction and verification of the risk prediction model of pressure injury in different specialties,the training of machine leaning algorithms and nursing education research.