Documenting and predicting topic changes in Computers in Biology and Medicine: A bibliometric keyword analysis from 1990 to 2017

FAUST, Oliver (2018). Documenting and predicting topic changes in Computers in Biology and Medicine: A bibliometric keyword analysis from 1990 to 2017. Informatics in Medicine Unlocked, 11, 15-27.

[img]
Preview
PDF
1-s2.0-S2352914818300534-main.pdf - Published Version
Creative Commons Attribution Non-commercial No Derivatives.

Download (1MB) | Preview
Related URLs:

    Abstract

    The Computers in Biology and Medicine (CBM) journal promotes the use of computing machinery in the fields of bioscience and medicine. Since the first volume in 1970, the importance of computers in these fields has grown dramatically, this is evident in the diversification of topics and an increase in the publication rate. In this study, we quantify both change and diversification of topics covered in. This is done by analysing the author supplied keywords, since they were electronically captured in 1990. The analysis starts by selecting 40 keywords, related to Medical (M) (7), Data (D) (10), Feature (F) (17) and (AI) (6) methods. Automated keyword clustering shows the statistical connection between the selected keywords. We found that the three most popular topics in CBM are: Support Vector Machine (SVM), Electroencephalography (EEG) and IMAGE PROCESSING. In a separate analysis step, we bagged the selected keywords into sequential one year time slices and calculated the normalized appearance. The results were visualised with graphs that indicate the CBM topic changes. These graphs show that there was a transition from Artificial Neural Network (ANN) to SVM. In 2006 SVM replaced ANN as the most important AI algorithm. Our investigation helps the editorial board to manage and embrace topic change. Furthermore, our analysis is interesting for the general reader, as the results can help them to adjust their research directions.

    Item Type: Article
    Uncontrolled Keywords: Research trends ; Topic analysis ; Topic detection and tracking ; Text mining ; Computers in biology and medicine
    Research Institute, Centre or Group - Does NOT include content added after October 2018: Materials and Engineering Research Institute > Engineering Research
    Departments - Does NOT include content added after October 2018: Faculty of Science, Technology and Arts > Department of Engineering and Mathematics
    Page Range: 15-27
    Depositing User: Oliver Faust
    Date Deposited: 02 Oct 2018 11:26
    Last Modified: 17 Jun 2020 16:41
    URI: http://shura.shu.ac.uk/id/eprint/22513

    Actions (login required)

    View Item View Item

    Downloads

    Downloads per month over past year

    View more statistics