[1]谭斯允,黄开颜.7种生物医学工程学类中国科技核心期刊2018-2020年主要发文指标分析[J].医学信息,2023,36(11):27-32.[doi:10.3969/j.issn.1006-1959.2023.11.005]
 TAN Si-yun,HUANG Kai-yan.Analysis of Main Publication Indexes of 7 Kinds of Core Scientific and Technological Journal of China in Biomedical Engineering Category from 2018 to 2020[J].Journal of Medical Information,2023,36(11):27-32.[doi:10.3969/j.issn.1006-1959.2023.11.005]
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7种生物医学工程学类中国科技核心期刊2018-2020年主要发文指标分析()
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医学信息[ISSN:1006-1959/CN:61-1278/R]

卷:
36卷
期数:
2023年11期
页码:
27-32
栏目:
医学数据科学
出版日期:
2023-06-01

文章信息/Info

Title:
Analysis of Main Publication Indexes of 7 Kinds of Core Scientific and Technological Journal of China in Biomedical Engineering Category from 2018 to 2020
文章编号:
1006-1959(2023)11-0027-06
作者:
谭斯允黄开颜
(南方医科大学《中国医学物理学杂志》编辑部,广东 广州 510515)
Author(s):
TAN Si-yunHUANG Kai-yan
(Editorial Department of Chinese Journal of Medical Physics,Southern Medical University,Guangzhou 510515,Guangdong,China)
关键词:
中国科技核心期刊生物医学工程学中国医学物理学杂志文献计量学
Keywords:
Core scientific and technological journal of ChinaBiomedical engineeringChinese Journal of Medical PhysicsBibliometrics
分类号:
G353.1
DOI:
10.3969/j.issn.1006-1959.2023.11.005
文献标志码:
A
摘要:
目的 分析生物医学工程学类中国科技核心期刊2018-2020年主要发文指标,挖掘生物医学工程学的研究热点,为提升期刊质量及影响力提供参考。方法 从2019-2021年版《中国科技期刊引证报告(核心版)》中选取具有可比性的生物医学工程学类中国科技核心期刊,共纳入7种期刊,分别是《北京生物医学工程》《生物医学工程学杂志》《生物医学工程研究》《生物医学工程与临床》《中国生物医学工程学报》《中国医学物理学杂志》《中华生物医学工程杂志》。分析上述7种期刊的发文量、地区分布数、机构分布数及高产机构、平均作者数、平均引文数、基金论文比,并对期刊的高频关键词以及部分期刊中被引频次最高的论文进行分析。结果 7种期刊的地区分布数为13~28,机构分布数为42~193,平均作者数为3.9~5.0,平均引文数为15.2~35.7,基金论文比为0.26~0.98,间接反映了不同期刊的论文质量存在着较大的差异。7种期刊在2018~2020年发文量排名前10的机构均为高校;《生物医学工程学杂志》《中国生物医学工程学报》及《中国医学物理学杂志》在CSCD中被引频次最高的论文均与深度学习有关。相较其他期刊,《中国医学物理学杂志》的发文量、地区分布数、机构分布数均具有明显优势,但平均引文数及基金论文比仍不理想。结论 纳入的7种生物医学工程学类中国科技核心期刊的高产发文机构均为高校,但是不同期刊的论文质量存在较大的差异;深度学习为生物医学工程学领域近年来的研究热点,是重要的组稿方向之一。《中国医学物理学杂志》可通过发表有关深度学习的优质论文、提高基金论文比等措施来提升期刊质量、提高期刊影响力。
Abstract:
Objective To analyze the main publication indexes of core scientific and technological journal of China in the biomedical engineering category from 2018 to 2020 for mining the research hotspots of biomedical engineering, and providing references for improving the quality and influence of journals.Methods A total of 7 comparable journals in biomedical engineering category were extracted from the 2019-2021 editions of the Chinese S&T Journal Citation Reports, namely Beijing Biomedical Engineering, Journal of Biomedical Engineering, Journal of Biomedical Engineering Research, Biomedical Engineering and Clinical Medicine, Chinese Journal of Biomedical Engineering, Chinese Journal of Medical Physics, Chinese Journal of Biomedical Engineering. The total number of papers, regional distribution, institutional distribution and productive institutions, average number of authors, average number of citations and ratio of funded papers of the above 7 journals were analyzed. Moreover, the high-frequency keywords and most frequently cited papers in some journals were also analyzed.Results The author affiliation in the 7 journals covered 13-28 regions and 42-193 institutions, and the average number of authors, average number of citations and ratio of funded papers were 3.9-5.0, 15.2-35.7 and 0.26-0.98, respectively, which indirectly reflected that there were significant differences in the quality of papers published in different journals. The top 10 institutions in the number of papers published in the 7 journals from 2018 to 2020 were all colleges and universities. The most frequently cited papers of Journal of Biomedical Engineering, Chinese Journal of Biomedical Engineering and Chinese Journal of Medical Physics in CSCD were related to deep learning. Compared with other journals, Chinese Journal of Medical Physics had obvious advantages in the number of papers, regional distribution and institutional distribution, but its average number of citations and the ratio of funded papers were still unsatisfactory.Conclusion For the 7 kinds of core scientific and technological journals of China in the biomedical engineering category, the most productive institutions are colleges and universities, but the quality of papers differed significantly among different journals. Deep learning, as a research hotspot of biomedical engineering in recent years, is one of the important sources of contributions. Chinese Journal of Medical Physics can enhance its quality and influence by publishing high-quality papers on deep learning and improving the ratio of funded papers, etc.

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更新日期/Last Update: 1900-01-01