ArticleInterdisciplinary perspectives on infectious diseases2022
Detecting Latent Topics and Trends in Global Publications on Brucellosis Disease Using Text Mining.
Article in Interdisciplinary perspectives on infectious diseases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Unsupervised learning and natural language processing highlight research trends in a superbug.Frontiers in artificial intelligence · 2024Article
- Topic Analysis and Mapping of Tuberculosis Research Using Text Mining and Co-Word Analysis.Tuberculosis research and treatment · 2022Article
- Mapping the Global Landscape of Antibiotic-Resistant Brucellosis Research: An LDA Topic Modeling and Text Analysis.Inquiry : a journal of medical care organization, provision and financingArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeBrucellosis 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.
methodsThis 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.
resultsAccording 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.
conclusionThis 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.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.