Deep learning applied in epilepsy: Bibliometric and visual analysis
This study innovatively employs bibliometric methods to visually analyze research on DL applications in epilepsy, which reveals a rising trend in research within the field and identifies key hotspots, such as DL in seizure detection and prediction. The potential of DL to enhance epilepsy management is highlighted, particularly in improving the accuracy of seizure detection and prediction, thereby enhancing patients' quality of life. Furthermore, the findings highlight the importance of increasing seizure prediction accuracy, exploring multimodal data integration, and developing more interpretable DL models for future research.
Authors
- Wu Yiman
- Wu Wenqi
Institutions
- Wenzhou University (CN)
- Jiangsu Vocational College of Medicine (CN)
- Wenzhou University of Technology
Publication Details
- Journal
- Digital Health
- Published
- 2025-05-01
- DOI
- https://doi.org/10.1177/20552076251375840
- Primary Topic
- EEG and Brain-Computer Interfaces
- Type
- article
- Field-Weighted Citation Impact
- 0.00