BP神经网络用于肝炎患者舌诊近红外光谱的研究

为了对肝炎患者进行快速无创检测,用BP人工神经网络(ANN)方法在健康人与肝炎患者之间对人体舌面近红外光谱的反射率的关系进行关联方面的研究。分别采集了健康人和肝炎患者的舌左边、舌右边、舌下左边络脉、舌下右边络脉以及舌尖各部位各25例受试者的光谱数据,构造了一个3层神经网络结构,将所采集的各光谱数据进行归一化反射率预处理后作为神经网络的输入,建立了BP神经网络模型,分别选取对应的各个部位的40例作为训练样本集,用剩下的10例未知的样本进行预测,各部位测试的结果其相对偏差均在0.2以下,分类正确率为100%,达到满意的预测精度。结果表明提出的BP神经网络用于光谱舌诊进行无创检测识别不同病证提供了重要的参考价值。

Study on near infrared spectrum in the application of the BP neural network in the tongue diagnosis for hepatitis patients

For a quick and noninvasive examination of the tongue for potential hepatitis patients, a study was conducted on the relation between the reflectivity of near infrared spectrum on the tongues of the healthy people and the hepatitis patients. Spectral data, 25 items for each case, are to be collected from the left and right side tongue, left and right sublingual venae, and tip of the tongue from the healthy people and the hepatitis patients. Then a three-layer neural network structure was established with all the data input after normalization reflectivity pretreatment. With the establishment of a BP neural network model, 40 data from each part of the body were selected as training samples. The rest 10 were adopted for prediction, which later was proved to be 100% correct with relative deviation values of less than 0.2. The research findings show that the proposed application of BP neural network in the spectral noninvasive examination of the tongue for identification of different case diagnosis is important for reference.