Towards precision medicine: Application of the structural causal model in psychiatry
LEARNING POINTS The structural causal model (SCM) is a next‐generation artificial intelligence method. It can transparently reveal the causal graph of a system, make predictions based on causal mechanisms, enable individualised inference and facilitate virtual intervention experiments. Each SCM method has its own advantages and limitations that should be considered in practice. As the field develops rapidly, further breakthroughs in both SCM methods and precision medicine are anticipated. Currently, there are only a few applications of SCM in psychiatry research. We encourage the use of it as a tool for advancing precision medicine in psychiatry.
Authors
- Jijun Wang (ORCID: https://orcid.org/0000-0001-5427-7425)
- Shengying Qin (ORCID: https://orcid.org/0000-0002-8458-5960)
- Chunling Wan (ORCID: https://orcid.org/0000-0002-0372-0041)
- Liya Sun (ORCID: https://orcid.org/0000-0001-5243-4028)
- Ruichu Cai (ORCID: https://orcid.org/0000-0001-8972-167X)
- Chunbo Li (ORCID: https://orcid.org/0000-0002-3387-4439)
- Wei Chen (ORCID: https://orcid.org/0000-0002-8213-0567)
- Fangyu Chen
- Chen Zhang (ORCID: https://orcid.org/0009-0004-2706-4888)
- Fanyuan Zhang (ORCID: https://orcid.org/0009-0007-8466-8487)
Institutions
- Guangdong University of Technology (CN)
- Shanghai Jiao Tong University (CN)
- Shanghai Mental Health Center (CN)
- Wuhu Fourth People Hospital (CN)
Publication Details
- Journal
- General Psychiatry
- Published
- 2026-09-16
- DOI
- https://doi.org/10.1002/gps3.70053
- Primary Topic
- Mental Health Research Topics
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- National Science and Technology Major Project
- National Outstanding Youth Science Fund Project of National Natural Science Foundation of China
- Basic and Applied Basic Research Foundation of Guangdong Province