ViT-Based Face Diagnosis Images Analysis for Schizophrenia Detection
Our method fully leverages semantic feature representations of first-introduced face diagnosis images in SZ, offering strong interpretability and visualization capabilities. It not only opens a new path for SZ detection but also brings new tools and concepts to the research and application in the field of mental illness.
Authors
- Xiaohan Zhang (ORCID: https://orcid.org/0000-0002-3693-8194)
- Fufeng Li (ORCID: https://orcid.org/0000-0002-0566-3589)
- Runmin Cao (ORCID: https://orcid.org/0009-0005-5659-8042)
- Zhumei Sun
- Kai Gao (ORCID: https://orcid.org/0000-0003-3713-6035)
- Hua Xu (ORCID: https://orcid.org/0000-0002-7401-307X)
- Lijuan Wang (ORCID: https://orcid.org/0000-0002-2517-2728)
- Huilin Liu (ORCID: https://orcid.org/0000-0002-7912-2611)
- Yifan Wang (ORCID: https://orcid.org/0000-0003-1663-3120)
- Peng Qian (ORCID: https://orcid.org/0000-0002-9895-8027)
- Songze Li (ORCID: https://orcid.org/0000-0002-7892-8242)
- Xirong Sun
Institutions
- Tongji University (CN)
- Hebei University of Science and Technology (CN)
- Shanghai University of Traditional Chinese Medicine (CN)
- Tsinghua University (CN)
Publication Details
- Journal
- Brain Sciences
- Published
- 2024-12-29
- DOI
- https://doi.org/10.3390/brainsci15010030
- Citations
- 5
- Primary Topic
- Face recognition and analysis
- Type
- article
- Field-Weighted Citation Impact
- 1.25
Funders
- National Natural Science Foundation of China