Severity measurements using neural networks

Su-wen Chen, M. Evens, D. Trace, F. Naeymi-Rad
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Abstract

The authors introduce a novel patient severity measurement model using neural networks. A three layer, fully connected backpropagation neural network was used in the pilot experiment. The results are promising and demonstrate that the backpropagation neural network technique is capable of assessing the severity value by learning from raw data. The neural network is easy to improve and of relatively low cost. It saves the expert's valuable time used in assigning numerical values to variables.<>
使用神经网络进行严重性测量
提出了一种基于神经网络的患者严重程度测量模型。实验采用了三层全连接反向传播神经网络。结果表明,反向传播神经网络技术能够通过从原始数据中学习来评估严重程度值。神经网络易于改进,成本相对较低。它节省了专家在为变量赋值时所花费的宝贵时间。
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