Prediction of acute kidney injury after noncardiac surgery in intensive care unit by machine learning
NCS-AKI had a high incidence in the SICU, and AKI patients had a lower 28-day survival rate than non-AKI patients do. The SVM had a better ability to predict early postoperative AKI.
Authors
- Zhi‐Qiang Shi (ORCID: https://orcid.org/0000-0002-2980-4243)
- Mingli Zhu (ORCID: https://orcid.org/0000-0002-0070-4556)
- Zimin Song (ORCID: https://orcid.org/0000-0003-0248-6748)
- Ting Yang (ORCID: https://orcid.org/0000-0001-9560-4576)
- Tianyi Ai (ORCID: https://orcid.org/0000-0003-1342-8279)
- Jianxiao Chen (ORCID: https://orcid.org/0000-0001-9808-9549)
- Jiajia Tang (ORCID: https://orcid.org/0000-0001-6036-6133)
- Weijun Zhang (ORCID: https://orcid.org/0000-0002-9432-7404)
- Weiyan Zheng
- Peng Shao
- An Shi
Institutions
- Shanghai Jiao Tong University (CN)
- Renji Hospital (CN)
- Online Technologies (United States) (US)
Publication Details
- Journal
- Annals of Medicine and Surgery
- Published
- 2025-08-12
- DOI
- https://doi.org/10.1097/ms9.0000000000003699
- Primary Topic
- Hemodynamic Monitoring and Therapy
- Type
- article
- Field-Weighted Citation Impact
- 0.00