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使用机器学习方法预测急性损伤预后:系统性审查

Yu Lin1,2,3, Tongyue Shi1,2,4, Guilan Kong1,2,4

  • 1National Institute of Health Data Science, Peking University, Beijing, China.

Kidney medicine
|January 6, 2025
PubMed
概括

机器学习模型在预测急性损伤 (AKI) 死亡率方面表现有前途,优于传统方法. 然而,它们在预测功能恢复方面的准确性需要改进,以便做出更好的临床决策.

关键词:
艾基 (AKI) 是一个人.急性损伤是什么?急性损伤是什么?行政数据库的管理数据库.临床结果的临床结果.深度学习是一种深度学习.电子健康记录是电子健康记录.电子医疗记录 电子医疗记录机器学习是机器学习.预后 预后 预后

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