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Detecting Latent Topics and Trends in Global Publications on Brucellosis Disease Using Text Mining.

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  • معلومة اضافية
    • نبذة مختصرة :
      Purpose. Brucellosis is widespread globally and one of the most important zoonotic diseases. Therefore, to fully comprehend the disease and discover ways of prevention and treatment, researchers have conducted some research in this field. Hence, this study will focus on the topic trend of scientific publications of brucellosis. Methods. This study is an applied research using text mining techniques with an analytical approach. The statistical population of the present research is all global publications related to brucellosis. For data extraction, the Scopus citation database was used in the period from 1900 to 2020. The main keywords for search strategy design have been extracted from consultation with thematic specialists and using MESH. Python programming language has been applied to analyze data and implement text mining algorithms. Results. According to results, eight main topics of "Prevention," "Clinical symptoms," "Diagnosis," "Control," "Treatment," "Immunology," "Structural Features," and "Pathogenicity" have been identified for brucellosis publications. Moreover, the topics "Prevention" and "Pathogenicity" had the highest and lowest prevalence in the field of brucellosis over time, respectively. Conclusion. This study has revealed the topics published in the global publications of brucellosis; the findings can be useful for research centers and universities in determining research priorities in the field of brucellosis. [ABSTRACT FROM AUTHOR]
    • نبذة مختصرة :
      Copyright of Interdisciplinary Perspectives on Infectious Diseases is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)