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开发基于机器学习的急性损伤预测模型,在资源有限的环境中使用非标准的EMR

Shengwen Guo1,2, Yuanhan Chen3,4, Yu Kuang5

  • 1Department of Intelligent Science and Engineering, School of Automation Science and Engineering, South China University of Technology, Guangzhou, Guangdong, China.

Medical physics
|September 30, 2025
PubMed
概括

预测急性损伤 (AKI) 是可能使用非标准的电子病历 (EMR) 没有血清肌素 (SCr) 数据. 这种机器学习方法为资源有限的环境提供了至关重要的解决方案.

关键词:
急性脏损伤急性脏损伤是什么早期预测 早期预测在医院住院的患者.增强光度梯度的机器可以提高光度.低收入和中等收入国家.非标准的医疗记录

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