A novel machine learning approach for prediction of postoperative delirium using multi-domain features of high-density EEG
HD-EEG data can be used to establish high-quality ML models for POD predictions. Multidomain features enable more comprehensive integration of EEG information related to delirium. The feature space structure significantly affects the performance of the prediction model, with the linear model offering distinct advantages in predicting POD.
Authors
- Zhenhu Liang
- Juan Wang (ORCID: https://orcid.org/0000-0002-1596-2179)
- Mengmeng Tang
- Fan Wu
- Yuanyuan Zou
- Jianhui Liu
- Xinxin Cui
- Bowen Yu
Institutions
- Tongji University (CN)
- Shanghai Medical College of Fudan University (CN)
- Yanshan University (CN)
- Fudan University Shanghai Cancer Center (CN)
- Tongji Hospital (CN)
Publication Details
- Journal
- Biomedical Physics & Engineering Express
- Published
- 2026-04-15
- DOI
- https://doi.org/10.1088/2057-1976/ae5f98
- Primary Topic
- Intensive Care Unit Cognitive Disorders
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Hebei Province