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Study on FOA_BP remote sepsis diagnosis based on wireless sensor network

机译:基于无线传感器网络的FOA_BP远程败血症诊断研究

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摘要

With the development of economic level and growth in the living standard, how to enhance the accuracy and efficiency of remote sepsis diagnosis has become the key issue and hot topic in the current medical research. As the traditional BP neural network is poor in the generalization ability and needs a large number of samples, we proposed the study on remote sepsis diagnosis by using the FOA-optimized BP neural network. Besides, based on the wireless sensor network and ZigBee network, we constructed the mathematical model of FOA_BP remote sepsis diagnosis based on wireless sensor network. The sepsis data set of School of Medicine and Public Health, University of Wisconsin was used as the object of study. The FOA-BP algorithm is significantly superior to the BP neural network algorithm in the diagnosis accuracy, verifying the validity and reliability of making a sepsis diagnosis with FOA_BP. Therefore, the method can be popularized to other fields to solve other similar problems.
机译:随着经济水平的提高和生活水平的提高,如何提高远程败血症诊断的准确性和效率已成为当前医学研究的重点和热点。由于传统的BP神经网络泛化能力差且需要大量样本,因此提出了使用FOA优化的BP神经网络进行远程败血症诊断的研究。此外,基于无线传感器网络和ZigBee网络,建立了基于无线传感器网络的FOA_BP远程败血症诊断的数学模型。威斯康星大学医学院和公共卫生学院的败血症数据集被用作研究对象。 FOA-BP算法在诊断准确性方面显着优于BP神经网络算法,验证了使用FOA_BP进行败血症诊断的有效性和可靠性。因此,该方法可以推广到其他领域以解决其他类似问题。

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