基于知识图谱的自闭症谱系障碍研究主题分析

An Analysis of Research Topics on Autism Spectrum Disorder Based on Knowledge Graph

自闭症是一种广泛性发育障碍的疾病,近几年的自闭症患者数量不断增加。该文选取自闭症相关研究文献,从PubMed数据库中抽取自闭症相关文献,通过发文量统计发现自闭症研究文献呈现指数上涨趋势且在2016年达到顶峰。运用词频分析法截取相关高频词制作关键词词云发现随着自闭症患者年龄的不断增长,研究者较为关注自闭症的共病问题。利用中心性分析、共词分析和社会网络分析方法,通过VOSviewer可视化软件形成了6个研究主题的聚类,分别为自闭症的相关基础理论研究、致病因素研究、表型症状研究、临床诊断研究、干预措施研究、共病研究,并基于知识图谱对自闭症研究相关文献进行主题分析,从发文量和研究热点角度探究自闭症的研究现状及发展趋势,为科研人员提供参考依据。

Autism is a disease of widespread developmental disorders.In recent years,the number of patients with autism has been increasing.This article selects autism-related research literature and extracts autism-related literature from the PubMed database.Through the statistics of the number of publications,it is found that the autism research literature has an exponential upward trend and reached its peak in 2016.Using word frequency analysis to intercept relevant high-frequency words to create a keyword word cloud found that as the age of autistic patients continues to grow,researchers pay more attention to the comorbidity of autism.Using centrality analysis,co-word analysis,and social network analysis methods,clusters of 6 research topics were formed through the VOSviewer visualization software,which are related to basic theoretical research on autism,pathogenic factors,phenotypic symptoms,and clinical trials.Diagnosis research,intervention research,comorbidity research,and based on the knowledge map to conduct thematic analysis of autism research related literature,explore the current status and development trend of autism research from the perspective of the number of articles and research hotspots,and provide reference for scientific researchers.