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Cited by in CrossRef
For: Zhu K, Zhang ZX, Zhang M. Application value of machine learning models in predicting intraoperative hypothermia in laparoscopic surgery for polytrauma patients. World J Clin Cases 2024; 12(24): 5513-5522 [PMID: 39188615 DOI: 10.12998/wjcc.v12.i24.5513]
URL: https://www.wjgnet.com/2307-8960/full/v12/i24/5513.htm
Number Citing Articles
1
Mingming Lu, Tingting Liu, Jian Wang, Liu Wang, Hui Ni. The impact of preoperative nutritional status, intraoperative fluid administration volume, operating room temperature, and anesthesia duration on intraoperative hypothermia in elderly patients undergoing total joint replacement under general anesthesia: a logistic regression analysis and nursing intervention strategiesFrontiers in Medicine 2026; 12 doi: 10.3389/fmed.2025.1672165
2
Wenyu Su, Xiaoli Wang, Huiyu Jia, Wenjing Chang, Shan Jiang, Huaiju Ge, Shihong Dong, Jie Yu, Guifeng Ma, Yingtao Meng. Explainable prediction of hypothermia risk in laparoscopic surgery: a retrospective cross-sectional study using machine learningBMC Surgery 2025; 25(1) doi: 10.1186/s12893-025-03071-9
3
Likui Huang, Yanqing Xu, Shaohua Chen, Juanjuan Zhang, Shuwei Weng. Development and validation of a machine learning-based prediction model for intraoperative hypothermia in Chinese patients undergoing gastrointestinal surgeryPerioperative Medicine 2025; 14(1) doi: 10.1186/s13741-025-00587-9
4
Yan Cheng, Huasong Sheng. Risk factors and predictive modeling of intraoperative hypothermia in laparoscopic surgery patientsBMC Surgery 2025; 25(1) doi: 10.1186/s12893-025-03186-z