[人工神经网络在医院感染风险预测中的应用]
[Artificial neural network in the prediction of nosocomial infection risk].
作者信息
Xu Lin-yong, Bai Yi, Hu Ming, Xu Yong-yong, Sun Zhen-qiu
机构信息
Department of Health Statistics, Xiangya School of Public Health, Central South University, Changsha, China.
出版信息
Zhong Nan Da Xue Xue Bao Yi Xue Ban. 2006 Jun;31(3):404-7.
OBJECTIVE
To establish a model based on artificial neural network in the prediction of nosocomial infection risk.
METHODS
Clinical data of 27,352 inpatients extracted from hospital information system were cleaned and coded, and the model of prediction in nosocomial infection risk was developed based on artificial neural network.
RESULTS
The structure of artificial neural network is {16-6-1}-BP, and the fit rate of prediction was 0.9891. The area under ROC curve was 0.986.
CONCLUSION
Artificial neural network model can be used as a tool for nosocomial infection forecasting, which can provide supplementary information for the diagnosis and control of nosocomial infection.
目的
建立基于人工神经网络的医院感染风险预测模型。
方法
从医院信息系统中提取27352例住院患者的临床数据进行清理和编码，并基于人工神经网络建立医院感染风险预测模型。
结果
人工神经网络结构为{16 - 6 - 1}-BP，预测拟合率为0.9891，ROC曲线下面积为0.986。
结论
人工神经网络模型可作为医院感染预测工具，可为医院感染的诊断和控制提供补充信息。
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