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An accurate mortality prediction method based on decision-level fusion of existing ICU scoring systems

机译：一种基于决策级融合的现有ICU评分系统的精确死亡率预测方法

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摘要

In this paper, we propose a mortality prediction method based on decision-level fusion (DLF) of existing intensive unit care (ICU) scoring systems. First, the proposed method obtains severity scores from the existing ICU scoring systems. Furthermore, we construct classifiers that categorize patients into survivors or non-survivors. Next, patient feature vectors are extracted based on the mortality rates that are estimated from the obtained severity scores by using a non-linear least squares method to obtain other types of classification results. In order to obtain the final severity score for each patient, we integrate the obtained multiple classification results based on DLF that can estimate the final severity scores. Finally, we performed the proposed method to actual ICU patient data and verified the effectiveness of the proposed method. Thus, the proposed method can realize accurate mortality prediction without any additional work by using the existing ICU scoring systems.
机译：在本文中，我们提出了一种基于现有重症监护（ICU）评分系统的决策级融合（DLF）的死亡率预测方法。首先，所提出的方法从现有的ICU评分系统中获得严重性评分。此外，我们构建了将患者分为幸存者或非幸存者的分类器。接下来，通过使用非线性最小二乘法从获得的严重性评分中估算出的死亡率中提取患者特征向量，以获得其他类型的分类结果。为了获得每个患者的最终严重程度评分，我们基于DLF集成了获得的多个分类结果，这些结果可以估计最终严重程度评分。最后，我们对实际ICU患者数据执行了所提出的方法，并验证了所提出方法的有效性。因此，通过使用现有的ICU评分系统，所提出的方法无需任何额外的工作即可实现准确的死亡率预测。

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