Bibliometric analysis on Deep Brain StimulationProcedures Conducted Between 2000-2023
Bibliographic record
Abstract
Objective: Deep brain stimulation (DBS) is a treatment method that uses electrodes to stimulate the brain, affecting brain activity and potentially causing medical conditions. It is commonly used to treat Parkinson's disease, essential tremor, dystonia, epilepsy, Tourette syndrome, and obsessive-compulsive disorder. This bibliometric study examines advanced bibliometric parameters in articles published since 2000, focusing on trends in publishing organizations, countries, funding sources, international collaborations, and trend keywords. Materials and Methods: We have searched the Web of Science database to find articles on DBS which published since 2000. The search was performed by using the MESH keywords releated to "Deep brain stimulation". Results: This study presents a comprehensive analysis of 4,601 articles on Deep Brain Stimulation (DBS) from 2000 to 2023, focusing on publication trends, properties, funding, country contributions, and international collaborations. Noteworthy findings include a peak of 413 publications in 2020 and 14,992 citations in 2021. The overall trajectory demonstrates a significant increase in scientific output, with an average of 31.9 citations per article. Publication properties reveal diverse access categories, including 66 Early Access and 2,136 Open Access articles. The majority of records are in the Science Citation Index Expanded (93.980%). Clinical Neurology dominates research topics with 63.464% representation. Funding sources highlight major contributions from the USA, Germany, and China. The USA leads in research output, while the University of Toronto tops institutions. Major journals include "Stereotactic and Functional Neurosurgery" and "Movement Disorders." Keyword analysis emphasizes common themes like "deep brain stimulation" and "Parkinson's disease." International collaborations involve researchers from 75 countries, with the USA leading in total link strength. This study contributes valuable insights into the global landscape of DBS research. Conclusion: This analysis highlights the dynamic nature of Deep Brain Stimulation research, highlighting global collaboration and diverse topics, emphasizing the crucial role of key countries, institutions, and journals.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.013 | 0.027 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".