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首页> 外文期刊>Journal of medical systems >Can neural network able to estimate the prognosis of epilepsy patients according to risk factors?
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Can neural network able to estimate the prognosis of epilepsy patients according to risk factors?

机译:神经网络能否根据危险因素估计癫痫患者的预后?

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The aim of this study is to evaluate the underlying etiologic factors of epilepsy patients and to predict the prognosis of these patients by using a Multi-Layer Perceptron Neural Network (MLPNN) according to risk factors. 758 patients with epilepsy diagnosis are included in this study. The MLPNNs were trained by the parameters of demographic properties of the patients and risk factors of the disease. The results show that the most crucial risk factor of the epilepsy patients was constituted by the febrile convulsion (21.9%), the kinship of parents (22.3%), the history of epileptic relatives (21.6%) and the history of head injury (18.6%). We had 91.1 % correct prediction rate for detection of the prognosis by using the MLPNN algorithm. The results indicate that the correct prediction rate of prognosis of the MLPNN model for epilepsy diseases is found satisfactory.
机译:这项研究的目的是评估癫痫患者的潜在病因,并根据危险因素使用多层感知器神经网络(MLPNN)预测这些患者的预后。这项研究包括758例癫痫诊断患者。通过患者的人口统计学参数和疾病的危险因素对MLPNN进行训练。结果表明,癫痫患者最关键的危险因素是高热惊厥(21.9%),父母的亲属(22.3%),癫痫病亲属史(21.6%)和头部受伤史(18.6) %)。通过使用MLPNN算法,我们有91.1%的正确预测率可用于检测预后。结果表明,MLPNN模型对癫痫病的正确预后预测率令人满意。

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