{"title":"抑郁症神经影像学中被引用最多的文章:1992年至2020年间被引用最多的100篇文章的文献计量学分析","authors":"Mustafa Salimeen, A. Issotina Zibrila, Mazen Musa","doi":"10.26502/jatr.32","DOIUrl":null,"url":null,"abstract":"Objectives: The goal of this study was to assess the current state and trends in neuroimaging for depression over the last four decades, using bibliometric analysis to give researchers fresh ideas for the future study area. Methods: The Web of Science Core Collection was used to pull papers about neuroimaging for depression published between 1992 and 2021. We utilized the included articles to look at data on neuroimaging and depression publications, countries, institutions, cited journals, cited authors, cited references, keywords, and citation bursts. Results: From 1992 to 2021, 5153 publications were pulled. In these last four decades, we selected the most prestigious journals, countries, institutions, and authors in neuroimaging modalities in depression. The keyword \"major depression disorder\" came in first for research discoveries with the most elevated citation burst. \"Neuroimaging,\" \"depression,\" \"bipolar,\" \"unipolar,\" and \"anxiety\" were the five hot themes in neuroimaging on depression. Conclusions: The findings of this bibliometric analysis provide insight into current research patterns in neuroimaging for depression, as well as the present status and trends of the last four decades, which may aid investigators in determining the field's current status hotspots, and frontier tendencies.","PeriodicalId":93773,"journal":{"name":"Journal of analytical techniques and research","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Most Cited Articles in Neuroimaging for Depression: A Bibliometric Analysis of the Top 100 Most Highly Cited Articles Between 1992 and 2020\",\"authors\":\"Mustafa Salimeen, A. Issotina Zibrila, Mazen Musa\",\"doi\":\"10.26502/jatr.32\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Objectives: The goal of this study was to assess the current state and trends in neuroimaging for depression over the last four decades, using bibliometric analysis to give researchers fresh ideas for the future study area. Methods: The Web of Science Core Collection was used to pull papers about neuroimaging for depression published between 1992 and 2021. We utilized the included articles to look at data on neuroimaging and depression publications, countries, institutions, cited journals, cited authors, cited references, keywords, and citation bursts. Results: From 1992 to 2021, 5153 publications were pulled. In these last four decades, we selected the most prestigious journals, countries, institutions, and authors in neuroimaging modalities in depression. The keyword \\\"major depression disorder\\\" came in first for research discoveries with the most elevated citation burst. \\\"Neuroimaging,\\\" \\\"depression,\\\" \\\"bipolar,\\\" \\\"unipolar,\\\" and \\\"anxiety\\\" were the five hot themes in neuroimaging on depression. Conclusions: The findings of this bibliometric analysis provide insight into current research patterns in neuroimaging for depression, as well as the present status and trends of the last four decades, which may aid investigators in determining the field's current status hotspots, and frontier tendencies.\",\"PeriodicalId\":93773,\"journal\":{\"name\":\"Journal of analytical techniques and research\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of analytical techniques and research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.26502/jatr.32\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of analytical techniques and research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.26502/jatr.32","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
目的:本研究的目的是评估过去四十年来抑郁症神经影像学的现状和趋势,使用文献计量学分析为研究人员提供未来研究领域的新思路。方法:使用Web of Science核心合集检索1992年至2021年间发表的关于抑郁症神经影像学的论文。我们利用纳入的文章来查看有关神经影像学和抑郁症出版物、国家、机构、被引期刊、被引作者、被引参考文献、关键词和引文爆发的数据。结果:1992 - 2021年共被检索文献5153篇。在过去的四十年中,我们选择了抑郁症神经成像模式中最负盛名的期刊、国家、机构和作者。关键词“重度抑郁症”在研究发现中排名第一,被引用次数最多。“神经影像学”、“抑郁症”、“双相情感障碍”、“单极情感障碍”和“焦虑”是抑郁症神经影像学的五大热门主题。结论:本文献计量学分析的结果提供了对抑郁症神经影像学研究模式的深入了解,以及过去40年的现状和趋势,这可能有助于研究者确定该领域的现状、热点和前沿趋势。
The Most Cited Articles in Neuroimaging for Depression: A Bibliometric Analysis of the Top 100 Most Highly Cited Articles Between 1992 and 2020
Objectives: The goal of this study was to assess the current state and trends in neuroimaging for depression over the last four decades, using bibliometric analysis to give researchers fresh ideas for the future study area. Methods: The Web of Science Core Collection was used to pull papers about neuroimaging for depression published between 1992 and 2021. We utilized the included articles to look at data on neuroimaging and depression publications, countries, institutions, cited journals, cited authors, cited references, keywords, and citation bursts. Results: From 1992 to 2021, 5153 publications were pulled. In these last four decades, we selected the most prestigious journals, countries, institutions, and authors in neuroimaging modalities in depression. The keyword "major depression disorder" came in first for research discoveries with the most elevated citation burst. "Neuroimaging," "depression," "bipolar," "unipolar," and "anxiety" were the five hot themes in neuroimaging on depression. Conclusions: The findings of this bibliometric analysis provide insight into current research patterns in neuroimaging for depression, as well as the present status and trends of the last four decades, which may aid investigators in determining the field's current status hotspots, and frontier tendencies.