Machine learning–based predictive model for post-stroke dementia
Our findings suggest that ML models, especially extreme gradient boosting, can best predict the risk of PSD.
Authors
- Wenmin Wang (ORCID: https://orcid.org/0000-0003-2664-4413)
- Hong Fan (ORCID: https://orcid.org/0009-0004-1309-1295)
- Zemin Wei (ORCID: https://orcid.org/0009-0002-2143-7773)
- Jinli Miao (ORCID: https://orcid.org/0000-0002-0589-1645)
- Chenghui Zhang (ORCID: https://orcid.org/0000-0003-2317-5930)
- Mengqi Li (ORCID: https://orcid.org/0000-0002-1171-5648)
Institutions
- Shaoxing University (CN)
- Shaoxing People's Hospital (CN)
- Tsinghua University (CN)
Publication Details
- Journal
- BMC Medical Informatics and Decision Making
- Published
- 2024-11-11
- DOI
- https://doi.org/10.1186/s12911-024-02752-4
- Citations
- 10
- Primary Topic
- Stroke Rehabilitation and Recovery
- Type
- article
- Field-Weighted Citation Impact
- 2.50
Funders
- Zhejiang Province Public Welfare Technology Application Research Project
- Science and Technology Program of Zhejiang Province