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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 Wisconsinwas 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. [ABSTRACT FROM AUTHOR]

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 ofWisconsinwas 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. [ABSTRACT FROM AUTHOR]