光学学报, 2018, 38 (7): 0717002, 网络出版: 2018-09-05   

基于BP神经网络的血红蛋白定量光学检测方法 下载: 995次

Quantitative Optical Detection Method of Hemoglobin Based on BP Neural Network
作者单位
南开大学现代光学研究所, 天津 300350
摘要
构建了基于BP神经网络的血红蛋白定量计算模型,其既可用于血红蛋白检测,又能成功地区分不同肿瘤疾病。建立了血红蛋白定量计算的双隐含层BP 神经网络模型,预测集的相关系数为0.9838,预测集的相对偏差为2.532%;利用该模型得到了乳腺肿瘤患者和白血病患者血清中血红蛋白的含量,结果显示两者浓度间存在极其显著性差异(P<0.001),预示该模型在区分肿瘤疾病方面具有潜在的应用价值。
Abstract
In this paper, we establish a quantitative model based on BP neural network to detect hemoglobin in serum, and put it into practice of hemoglobin measurement, in the result of which various cancer diseases can be completely distinguished. A double-hidden-layer BP neural network model to quantify hemoglobin is established. The correlation coefficient of the prediction set in the model is 0.9838, and its relative deviation is 2.532%. The hemoglobin concentrations in serum samples of breast cancer patients and leukemia patients are obtained by the BP neural network model. A remarkable difference appears in the concentrations between these two sorts of patients (P<0.001), indicating that the model has potential application in distinguishing tumor diseases.

王姗姗, 黄凯, 李铭, 陈平, 刘伟伟, 林列. 基于BP神经网络的血红蛋白定量光学检测方法[J]. 光学学报, 2018, 38(7): 0717002. Shanshan Wang, Kai Huang, Ming Li, Ping Chen, Weiwei Liu, Lie Lin. Quantitative Optical Detection Method of Hemoglobin Based on BP Neural Network[J]. Acta Optica Sinica, 2018, 38(7): 0717002.

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