A deep-learning model for predicting post-stroke cognitive impairment based on brain network damage
This study not only established a model that can accurately predict PSCI, it also identified potential targets for symptom-based treatments, offering new insights into PSCI.
Authors
- Xiuying Cai (ORCID: https://orcid.org/0000-0002-3496-3281)
- Jian Zheng (ORCID: https://orcid.org/0000-0003-4257-331X)
- Yilin Leng (ORCID: https://orcid.org/0000-0003-0354-2887)
- Yuefang Dong
- Li Tan (ORCID: https://orcid.org/0000-0002-2786-5958)
- Wenju Cui (ORCID: https://orcid.org/0000-0002-4304-536X)
- Lei Li (ORCID: https://orcid.org/0000-0002-1500-7446)
- Chen Bai (ORCID: https://orcid.org/0000-0002-5673-4033)
- Haixing Xiao
Institutions
- University of Science and Technology of China (CN)
- Chinese Academy of Sciences (CN)
- Soochow University (CN)
- Suzhou Institute of Biomedical Engineering and Technology (CN)
- First Affiliated Hospital of Soochow University (CN)
- Weihai Science and Technology Bureau (CN)
Publication Details
- Journal
- Quantitative Imaging in Medicine and Surgery
- Published
- 2025-04-30
- DOI
- https://doi.org/10.21037/qims-24-2010
- Citations
- 1
- Primary Topic
- Brain Tumor Detection and Classification
- Type
- article
- Field-Weighted Citation Impact
- 0.84