Development and clinical application of an automated machine learning-based delirium risk prediction model for emergency polytrauma patients
This study provides a trauma-specific, interpretable ML tool that integrates GCS scoring and dynamic biomarker monitoring, enabling early delirium risk identification in emergency polytrauma. The framework demonstrates feasibility for integration into clinical workflows to improve trauma care quality.
Authors
- Yihao Huang (ORCID: https://orcid.org/0000-0002-5784-770X)
- Yisha Xu
- Liang‐Jie Zhang (ORCID: https://orcid.org/0000-0002-6219-0853)
- Long Li (ORCID: https://orcid.org/0000-0002-1342-860X)
- Peng Wu (ORCID: https://orcid.org/0000-0003-2676-508X)
- Zhigang Zhang (ORCID: https://orcid.org/0000-0003-3057-4956)
- Ming Zhang (ORCID: https://orcid.org/0009-0000-2631-1622)
- Tingyong Han
- Zhenyi Liu (ORCID: https://orcid.org/0009-0004-6677-3994)
Institutions
- Ya'an Polytechnic College (CN)
- Yan'an University (CN)
- People's Liberation Army 401 Hospital (CN)
Publication Details
- Journal
- Frontiers in Physiology
- Published
- 2025-07-14
- DOI
- https://doi.org/10.3389/fphys.2025.1629329
- Citations
- 1
- Primary Topic
- Intensive Care Unit Cognitive Disorders
- Type
- article
- Field-Weighted Citation Impact
- 1.55