Study of thematic developments in data mining in the biomedical field of scopus database: by co-occurrence of words

Abstract

Introduction: Databases in the field of biomedicine contain a large amount of clinical data in which the discovery of connections and patterns can lead to new knowledge and have potential for service efficiency. Objective: The aim of this study was to study the thematic developments of datamining in the field of "biomedicine" in Scopus database between 2010 and 2019.

Methods and Materials: This research has been done using social network analysis and vocabulary coexistence. Bibexcel and Gephi software were used to analyze and plot the co-occurring vocabulary network and SciMAT software was used to draw strategic charts. Results: The results of the analysis of 7910 articles published and indexed in the Scopus database show the gentle growth of all scientific data mining products in the field of biomedicine and the fields of "genetics"، "expression-genes"، "proteins"، "Computational biology" are active research areas. Conclusion: Drawing scientific maps continuously helps policymakers in choosing research priorities and allocating funds، therefore، it is desirable that scientific disciplines be reviewed continuously. It is also necessary to pay attention to minor issues.