Functional MRI-based machine learning strategy for prediction of postoperative delirium in cardiac surgery patients: A secondary analysis of a prospective observational study
This study found that the random forest model using preoperative functional MRI data and clinical variables was accurate in identifying patients at high risk of developing delirium after cardiac surgery.
Authors
- Sen Bai (ORCID: https://orcid.org/0000-0002-7146-6970)
- Yangzi Zhu (ORCID: https://orcid.org/0000-0002-4709-4652)
- Jun‐Li Cao (ORCID: https://orcid.org/0000-0002-8932-4743)
- Wei Wang (ORCID: https://orcid.org/0000-0002-0488-4654)
- Liwei Wang (ORCID: https://orcid.org/0000-0002-5346-5886)
- Yan Zhang (ORCID: https://orcid.org/0000-0002-7329-0382)
- Wei Zhang (ORCID: https://orcid.org/0000-0002-4771-7573)
- Yao Lu (ORCID: https://orcid.org/0000-0003-4180-194X)
- Yibing Shi (ORCID: https://orcid.org/0000-0003-4954-313X)
- Meiyan Zhou (ORCID: https://orcid.org/0009-0003-7193-9242)
Institutions
- Xuzhou Medical College (CN)
- Xuzhou Central Hospital (CN)
Publication Details
- Journal
- Journal of Clinical Anesthesia
- Published
- 2025-02-13
- DOI
- https://doi.org/10.1016/j.jclinane.2025.111771
- Citations
- 4
- Primary Topic
- Intensive Care Unit Cognitive Disorders
- Type
- article
- Field-Weighted Citation Impact
- 6.18
Funders
- National Natural Science Foundation of China
- Ministry of Science and Technology of the People's Republic of China
- Jiangsu Provincial Commission of Health and Family Planning