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Topic Analysis and Mapping of Tuberculosis Research Using Text Mining and Co-Word Analysis
Meisam Dastani1, Alireza Mohammadzadeh2, Jalal Mardaneh2
1Infectious Diseases Research Center, Gonabad University of Medical Sciences, Gonabad, Iran.
Tuberculosis Research and Treatment
|November 18, 2022
Summary
This study analyzed global tuberculosis research trends from 1900-2022. Key topics include clinical symptoms, diagnosis and treatment, bacterial factors, and prevention strategies for this severe progressive disease.
Area of Science:
- Public Health
- Infectious Diseases
- Medical Informatics
Background:
- Tuberculosis (TB) remains a significant global health challenge, hindering social and economic progress.
- Understanding research trends is crucial for effective disease control and intervention strategies.
Purpose of the Study:
- To analyze the topic trends in scientific publications on tuberculosis.
- To identify the evolution of research focus over time using text mining and co-word analysis.
Main Methods:
- Utilized Scopus database for global publications on tuberculosis (1900-2022).
- Employed text mining and co-word analysis with Python and VOSviewer software.
- Keywords selected via expert consultation and Medical Subject Headings (MeSH).
Main Results:
- Identified four dominant research themes: Clinical symptoms (41.8%), Diagnosis and treatment (28.1%), Bacterial structure, pathogenicity and genetics (22.3%), and Prevention (7.84%).
- Highlighted the distribution and focus of scientific inquiry into tuberculosis over more than a century.
Conclusions:
- The findings provide insights into the historical trajectory of tuberculosis research.
- Informing strategic decisions, program development, and guideline creation for combating tuberculosis globally.
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