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Risk Factors for Apgar Score using Artificial Neural Networks

机译:使用人工神经网络进行Apgar评分的危险因素

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Artificial Neural Networks (ANNs) have been used in identifying the risk factors for many medical outcomes. In this paper, the risk factors for low Apgar score are introduced. This is the first time, to our knowledge, that the ANNs are used for Apgar score prediction. The medical domain of interest used is the perinatal database provided by the Perinatal Partnership Program of Eastern and Southeastern Ontario (PPPESO). The ability of the feed forward back propagation ANNs to generate strong predictive model with the most influential variables is tested. Finally, minimal sets of variables (risk factors) that are important in predicting Apgar score outcome without degrading the ANN performance are identified
机译:人工神经网络(ANN)已用于识别许多医疗结果的危险因素。本文介绍了Apgar评分低的危险因素。据我们所知,这是第一次将神经网络用于Apgar分数预测。所使用的医学领域是东部和东南安大略的围产期合作计划(PPPESO)提供的围产期数据库。测试了前馈反向传播ANN生成具有最大影响力变量的强大预测模型的能力。最后,确定了在不降低ANN性能的情况下对预测Apgar评分结果至关重要的最小变量集(风险因素)

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