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Updated: May 5, 2026
06:01
A Thrombotic Stroke Model Based On Transient Cerebral Hypoxia-ischemia
Published on: August 18, 2015
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Trends in stroke-related journals: Examination of publication patterns using topic modeling
Burak Berksu Ozkara1, Mert Karabacak2, Konstantinos Margetis2
1Department of Neuroradiology, MD Anderson Cancer Center, 1400 Pressler Street, Houston, bX, 77030, USA.
Summary
Natural language processing and topic modeling can effectively manage stroke research literature. Key prevalent topics include animal models and reperfusion therapy, with emerging trends in emboli and glucose metabolism.
Area of Science:
- Neuroscience and Neurology
- Biomedical Informatics
Background:
- Stroke research generates a vast volume of scholarly publications.
- Efficiently managing and interpreting this literature is crucial for advancing the field.
- Natural language processing (NLP) and topic modeling offer potential solutions.
Purpose of the Study:
- To demonstrate the utility of NLP and topic modeling in analyzing stroke research publications.
- To expedite literature reviews, uncover hidden research themes, and identify emerging trends.
- To provide insights into the evolving landscape of stroke research.
Main Methods:
- Analysis of 35,779 articles from five leading stroke journals (Stroke, IJOS, ESJ, TSR, JSCD) via Scopus database.
- Extraction of titles, abstracts, publication years, and citation counts.
- Application of BERTopic for topic modeling and linear regression for trend identification using Python 3.1.
Main Results:
- 26,732 documents were classified into 30 distinct topics.
- "Animal Models," "Rehabilitation," and "Reperfusion Therapy" emerged as the most prevalent topics.
- Trending topics included "Emboli," "Medullary and Cerebellar Infarcts," and "Glucose Metabolism."
Conclusions:
- NLP and topic modeling provide a robust methodology for understanding research evolution and specialization.
- Findings highlight the importance of animal models, growth in rehabilitation research, and the centrality of reperfusion therapy.
- Limitations include a restricted journal selection and dependence on metadata quality.
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