[1]刘 萍,张嘉鹏.基于知识图谱的MIMIC电子病历数据集的研究热点和趋势分析[J].医学信息,2023,36(07):67-73.[doi:10.3969/j.issn.1006-1959.2023.07.012]
　LIU Ping,ZHANG Jia-peng.Research Hotspots and Trend Analysis of MIMIC Electronic Medical Record Data Set Based on Knowledge Graph[J].Journal of Medical Information,2023,36(07):67-73.[doi:10.3969/j.issn.1006-1959.2023.07.012]
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基于知识图谱的MIMIC电子病历数据集的研究热点和趋势分析()
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医学信息[ISSN:1006-1959/CN:61-1278/R]

卷:
36卷
期数:
2023年07期
页码:
67-73
栏目:
医学数据科学
出版日期:
2023-04-01

文章信息/Info

Title:
Research Hotspots and Trend Analysis of MIMIC Electronic Medical Record Data Set Based on Knowledge Graph
文章编号:
1006-1959（2023）07-0067-07
作者:
刘 萍; 张嘉鹏
（1.中山大学附属第七医院重症医学科，广东 深圳 518000；2.嘉应学院医学院，广东 梅州 514021）
Author(s):
LIU Ping; ZHANG Jia-peng
(1.Department of Critical Medicine,the Seventh Affiliated Hospital,Sun Yat-sen University,Shenzhen 518000,Guangdong,China;2.College of Medcine,Jiaying University,Meizhou 514021,Guangdong,China)
关键词:
MIMIC; 知识图谱; CiteSpace; HistCite; VOSviewer; 电子病历
Keywords:
MIMIC; Knowledge map; CiteSpace; HistCite; VOSviewer; Electronic health record
分类号:
R319
DOI:
10.3969/j.issn.1006-1959.2023.07.012
文献标志码:
A
摘要:
目的 了解MIMIC电子病历数据集国内外研究热点和趋势。方法 利用CiteSpace、HistCite和VOSviewer软件，从发文量、发文机构、主要研究者、高被引期刊、高被引论文、研究主题6个纬度，对CBKI、Web of Science中有关MIMIC电子病历数据集的研究文献进行文献计量分析。结果 MIMIC领域内的发文量逐年递增；主要发文机构是美国的麻省理工学院和中国的浙江大学；主要研究作者是美国学者CELI LA；同行内高被引期刊为CRITICAL CARE MEDICINE；高被引论文是编号37号文献；研究主题2018年前主要是以MIMIC数据集患者行为研究为主，2019年以后主要集中于患者死亡危险因素分析；关键词聚类分析前期研究主要与患者心肺肾系统疾病相关，后期集中于急性肾损伤和MIMIC数据库数据完善研究。结论 MIMIC电子病历数据集的研究机构和研究者之间合作较少，国内相关研究也较少；研究主题局限于ICU患者死亡风险的预测和生存率的分析，应扩展主题研究；未来MIMIC研究趋势将侧重于结合AI技术深度挖掘临床电子病历数据。
Abstract:
Objective To understand the research hotspots and trends of MIMIC electronic medical record data sets at home and abroad.Methods CiteSpace, HistCite and VosViewer software were used to conduct a bibliometric analysis of the research literature on the MIMIC electronic medical record data set in CBKI and Web of Science from six latitudes: number of publications, institutions, major researchers, highly cited journals, highly cited papers, and research topics.Results The number of publications in the field of MIMIC was increasing year by year; the main publishing institutions were Massachusetts Institute of Technology in the United States and Zhejiang University in China; the main research author was American scholar CELI LA; the highly cited journal in the peer was CRITICAL CARE MEDICINE; highly cited paper was No.37 literature; the research topic was mainly based on the patient behavior research of MIMIC data set before 2018, and mainly focused on the analysis of patient death risk factors after 2019. Keyword cluster analysis showed that the previous studies were mainly related to cardiopulmonary and renal system diseases, and later studies were focused on acute kidney injury and MIMIC database data improvement.Conclusion There is less cooperation between research institutions and researchers in the MIMIC electronic medical record data set, and there are few related studies in China. The research topic is limited to the prediction of death risk and survival rate of ICU patients, and the research should be expanded. The future research trend of MIMIC will focus on the deep mining of clinical electronic medical record data with AI technology.

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更新日期/Last Update: 1900-01-01