Trends in biomedical informatics: automated topic analysis of JAMIA articles

被引：10

作者：

Han, Dong ^{[1
,2
]}

Wang, Shuang ^{[1
]}

Jiang, Chao ^{[1
,2
]}

Jiang, Xiaoqian ^{[1
]}

Kim, Hyeon-Eui ^{[1
]}

Sun, Jimeng ^{[3
]}

Ohno-Machado, Lucila ^{[1
]}

机构：

[1] Univ Calif San Diego, Hlth Syst Dept Biomed Informat, La Jolla, CA 92093 USA

[2] Univ Oklahoma, Sch Elect & Comp Engn, Tulsa, OK 74135 USA

[3] Georgia Inst Technol, Sch Computat Sci & Engn, Atlanta, GA 30313 USA

来源：

JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION | 2015年 / 22卷 / 06期

关键词：

biomedical informatics; medical subject headings; tensor factorization; citation analysis; bioinformatics; ELECTRONIC HEALTH RECORDS; CLINICAL DECISION-SUPPORT; DATA RESEARCH NETWORK; GENOME-WIDE ASSOCIATION; ADVERSE DRUG-REACTIONS; OF-THE-LITERATURE; IMAGING INFORMATICS; MEDICAL-RECORD; TENSOR FACTORIZATION; INTEGRATING BIOLOGY;

D O I：

10.1093/jamia/ocv157

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Biomedical Informatics is a growing interdisciplinary field in which research topics and citation trends have been evolving rapidly in recent years. To analyze these data in a fast, reproducible manner, automation of certain processes is needed. JAMIA is a "generalist" journal for biomedical informatics. Its articles reflect the wide range of topics in informatics. In this study, we retrieved Medical Subject Headings (MeSH) terms and citations of JAMIA articles published between 2009 and 2014. We use tensors (i.e., multidimensional arrays) to represent the interaction among topics, time and citations, and applied tensor decomposition to automate the analysis. The trends represented by tensors were then carefully interpreted and the results were compared with previous findings based on manual topic analysis. A list of most cited JAMIA articles, their topics, and publication trends over recent years is presented. The analyses confirmed previous studies and showed that, from 2012 to 2014, the number of articles related to MeSH terms Methods, Organization & Administration, and Algorithms increased significantly both in number of publications and citations. Citation trends varied widely by topic, with Natural Language Processing having a large number of citations in particular years, and Medical Record Systems, Computerized remaining a very popular topic in all years.

引用

页码：1153 / 1163

页数：11

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