Sex-specific infarct volume associations and early prediction of language impairment progression following stroke surgery: a network approach
This multimodal model, enhanced by network analysis, accurately predicts language impairment progression and highlights preoperative consciousness as a key mediator, supporting precision stroke rehabilitation by capturing complex predictor interrelationships.
Authors
- Zhonghai Tao
- Y. Chen (ORCID: https://orcid.org/0000-0003-3062-4589)
- Zhengbao Zhu (ORCID: https://orcid.org/0000-0001-5500-0014)
- Guodong Li (ORCID: https://orcid.org/0009-0008-9669-6642)
- Hui Zheng (ORCID: https://orcid.org/0000-0002-0494-1217)
- Zhaoliang Wu
- Shanshan Ma (ORCID: https://orcid.org/0000-0002-0780-4568)
- Yuhan Chen (ORCID: https://orcid.org/0000-0003-0695-0317)
- Bing Fu (ORCID: https://orcid.org/0000-0003-4734-2457)
- Bai-Hui Luo
Institutions
- Jiangsu University (CN)
- University of Science and Technology of China (CN)
- Zhejiang Normal University (CN)
- Shanghai Mental Health Center (CN)
- Guangdong University of Education (CN)
- The First People’s Hospital of Lianyungang (CN)
- Kangda College of Nanjing Medical University
- Nanjing Medical University (CN)
Publication Details
- Journal
- Frontiers in Neurology
- Published
- 2025-12-03
- DOI
- https://doi.org/10.3389/fneur.2025.1728433
- Primary Topic
- Machine Learning in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 0.00