Individualized multi-modal MRI biomarkers predict 1-year clinical outcome in first-episode drug-naïve schizophrenia patients
Our study highlighted the potential of individual-specific network parcellation in treatment resistant schizophrenia prediction and underscored the crucial role of feature attributes in predictive model accuracy.
Authors
- Su Lui (ORCID: https://orcid.org/0000-0003-3541-1769)
- Chenyang Yao (ORCID: https://orcid.org/0000-0001-7436-5991)
- Aoxiang Zhang (ORCID: https://orcid.org/0009-0005-6553-7380)
- Qiyong Gong (ORCID: https://orcid.org/0000-0002-5912-4871)
- Youjin Zhao (ORCID: https://orcid.org/0000-0002-3776-3170)
- Qian Zhang (ORCID: https://orcid.org/0000-0002-0450-261X)
- Ziyuan Zhao (ORCID: https://orcid.org/0009-0000-4742-4116)
- Jiao Qu
Institutions
- Capital Medical University (CN)
- Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
- Sichuan University (CN)
- West China Hospital of Sichuan University (CN)
- Zhongshan Hospital of Xiamen University (CN)
Publication Details
- Journal
- Frontiers in Psychiatry
- Published
- 2024-09-13
- DOI
- https://doi.org/10.3389/fpsyt.2024.1448145
- Citations
- 1
- Primary Topic
- Functional Brain Connectivity Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.34
Funders
- National Natural Science Foundation of China
- Sichuan University
- Fundamental Research Funds for the Central Universities
- West China Hospital, Sichuan University