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Updated: Jul 7, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
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Published on: January 11, 2020

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预测高度不平衡数据的护士周转率,使用合成少数人过量采样技术和机器学习算法

Yuan Xu1, Yongshin Park2, Ju Dong Park3

  • 1School of Maritime Economics and Management, Collaborative Innovation Center for Transport Studies, Dalian Maritime University, 1 Linghai Road, Dalian 116026, China.

Healthcare (Basel, Switzerland)
|December 22, 2023
PubMed
概括

预测护士轮流对于医疗保健质量至关重要. 机器学习,增强通过合成少数群体过量采样技术 (SMOTE),有效地识别关键因素,如年龄和工作时间影响护士离开.

关键词:
这是NSSRNN.在SMOTE中使用.在XGBoost中使用.机器学习是机器学习.护士周转率 护士周转率随机的森林随机的森林

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