| 光谱学与光谱分析 |
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| Study on Near Infrared Spectrum in the Application of the BP Neural Network in the Tongue Diagnosis for Hepatitis Patients |
| YAN Wen-juan1,2, ZHANG Jing1, HU Guang-qin3, ZHAO Jing1, LIN Ling1*, LU Xiao-zuo3, LI Gang1 |
1. State Key Laboratory of Precision Measurement Technology and Instruments, Tianjin University, Tianjin 300072, China
2. School of Physics&Electron Engineering, Yangtze Normal University, Chongqing 408100, China
3. Institute of Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 300193, China |
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Abstract 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.
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Received: 2009-11-26
Accepted: 2010-02-28
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Corresponding Authors:
LIN Ling
E-mail: linling@tju.edu.cn
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[1] ZHANG Qin，WANG Lei，DU Guang-li，et al(张 琴，王 磊，都广礼，等). Chinese Journal of Basic Medicine in Traditional Chinese Medicine(中国中医基础医学杂志)，2007，13(6)：416.
[2] ZENG Feng，ZHAO Ying(曾 凤，赵 莺). Gansu Journal of Traditional Chinese Medicine(甘肃中医)，2008，21(3)：52.
[3] Jiang Zhihao，Zhu Kai，Lu Xiaozuo，et al. Proceedings of 2008 IEEE International Symposium on IT in Medicine and Education，2008，12：287.
[4] YAO Qiang(姚 嫱). Liaoning Journal of Traditional Chinese Medicine(辽宁中医杂志)，2008，35(2)：163.
[5] WU Xi-liang，LU Xiao-zuo(伍喜良，陆小左). Tianjin Journal of Traditional Chinese Medicine(天津中医药)，2005，22(5)：388.
[6] XING Dong-xing, CHANG Qing-rui(邢东兴，常庆瑞). J. Infrared Millim. Waves(红外与毫米波学报)，2009，28(3)：207.
[7] JIANG Jia-kui，MA Yong-kun，FAN Xiao-bo，et al(蒋家奎，马永昆，范晓波，等). China Condiment(中国调味品)，2009，34(3)：112.
[8] MA Ding-ling，ZHANG Tie-qiang(马钉凌，张铁强). Chinese Journal of Spectroscopy Laboratory(光谱实验室)，2007，24(5)：914.
[9] Liu Fei，Zhang Fan，Jin Zonglai，et al. Nondestructive Prediction of Acetolactate Synthase of Oilseed Rape Leaves Using Visible/Near-Infrared Spectroscopy and BP Neural Networks. Proceedings of the Seventh International Conference on Machine Learning and Cybernetics，Kunming, 2008. 1335.
[10] GAO Jun，YAO Cheng，ZHANG Jun(高 俊，姚 成，章 俊). Journal of Analytical Science(分析科学学报)，2006，22(1)：71.
[11] BAI Ying-kui，SHEN Xuan-guo，DING Dong(白英奎，申铉国，丁 东). Laser ＆ Infrared(激光与红外)，2004，34(5)：354.
[12] ZHANG Hong-yan，ZHANG Lai-ming，CHEN Yue，et al(张洪艳，张来明，陈 月，等). Laser & Infrared(激光与红外)，2005，35(2)：96.
[13] Kamil Ríha，Radim Ciz. Searching for a New Mon-Invasive Method of Blood Circulation System Diagnostics. in: Third International Conference on Systems，2008，4：156.
[14] ZHANG De-feng(张德丰). Application and Design of Neural Networks in MATLAB(MATLAB神经网络应用设计). Beijing: China Machine Press(北京：机械工业出版社)，2009. 44.
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