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Expert system for predicting the early pregnancy with disorders using artificial neural network

机译:使用人工神经网络预测疾病早期怀孕的专家系统

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Pregnancy is an important moment of growth of the human being. In many case women do not know that she is being pregnant, this is one of the causes of miscarriage. For healthy pregnancy also need to be guarded by knowing abnormalities early in pregnancy. There are several early pregnancy disorder among others hyperemesis gravidarum, pre-eclampsia and eclampsia, hydatidiform mole, and ectopic pregnancy. In this research, we propose an expert system using Artificial Neural Network (ANN) and Back Propagation algorithm for predicting the pregnancy with disorders early. We used 172 medical records of patient with 17 input parameters and 5 output classes, among others normal early pregnancy, and 4 classes for pregnancy disorders. The experiment with training and testing process showed that ANN could be applied to predict the disorders pregnancy with percentage of accuracy around 78,248%. The percentage is got by 0,1 of learning rate value, 17 of neuron input layers, 50 of neuron hidden layers, 5 of neuron output layers, and 0,01 of error value.
机译:怀孕是人类成长的重要时刻。在许多情况下,妇女不知道自己正在怀孕,这是流产的原因之一。为了健康怀孕,还需要通过在怀孕初期了解异常情况来加以保护。除妊娠剧吐,先兆子痫和子痫,葡萄胎和异位妊娠外,还有几种早期妊娠疾病。在这项研究中,我们提出了一个使用人工神经网络(ANN)和反向传播算法的专家系统,可以早期预测患有疾病的妊娠。我们使用了172名患者的病历,其中有17种输入参数和5种输出类别,其中包括正常的早期妊娠,以及4种针对妊娠疾病的类别。训练和测试过程的实验表明,人工神经网络可用于预测妊娠疾病,准确率约为78248%。该百分比由学习率值的0.1,神经元输入层的17,神经元隐藏层的50,神经元输出层的5和误差值的0.01得出。

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