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Melancholia Diagnosis Based on Energy Medicine Information and CMAC Neural Network Approach

机译:基于能源医学信息和CMAC神经网络方法的忧郁诊断

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In this paper, a preliminary result about the melancholia diagnosis scheme based on the analyses of depression questionnaire and the meridian energy of human body is proposed. Firstly, a large amount data obtained from hospital, recorded the aged patients' depression rating scales and the 12 sets meridian energy signals, are sieved out three disease groups' patterns. Then, CMAC (Cerebellar Model Articulation Controller) neural network diagnosis architecture is built depending on the three disease groups' patterns. Thirdly, the selected patterns were utilized to train the CMAC neural network. Finally, inputting the 12 sets meridian energy signals of human body into CMAC neural network, the finished training neural network can be used to diagnose the possibility of people with melancholia or not.
机译:本文提出了基于抑郁症问卷分析的忧郁诊断计划及人体的子午线的初步结果。首先,从医院获得的大量数据记录了老年患者的抑郁率尺度和12套的子午线能量信号,被筛分出三种疾病群体的模式。然后,根据三种疾病群体的模式,构建了CMAC(小脑模型铰接控制器)神经网络诊断架构。第三,利用所选择的模式来训练CMAC神经网络。最后,输入12套人体的子午线能量信号进入CMAC神经网络,完成的训练神经网络可用于诊断忧郁的人的可能性。

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