Leveraging transformer models to predict cognitive impairment: accuracy, efficiency, and interpretability
The enhanced Transformer model offers superior accuracy and efficiency in predicting cognitive decline compared to traditional models. Its capacity to process both continuous and categorical data and its interpretability through attention mechanisms make it a promising tool for early detection of neurodegenerative diseases, potentially improving clinical decision-making and interventions.
Authors
- Mengyang Wang (ORCID: https://orcid.org/0009-0005-7812-7786)
- Xinhang Huang
- Junzhi Zhang (ORCID: https://orcid.org/0000-0002-5055-2941)
- Kai Ma (ORCID: https://orcid.org/0000-0001-7535-1313)
Institutions
- Tianjin University of Traditional Chinese Medicine (CN)
- China Agricultural University (CN)
Publication Details
- Journal
- BMC Public Health
- Published
- 2025-02-07
- DOI
- https://doi.org/10.1186/s12889-025-21762-z
- Citations
- 1
- Primary Topic
- EEG and Brain-Computer Interfaces
- Type
- article
- Field-Weighted Citation Impact
- 1.43