| 光谱学与光谱分析 |
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| Early Stage Diagnosis of Endometrial Cancer Based on Near Infrared Spectroscopy and Support Vector Machine |
| ZHAI Wei1，XIANG Yu-hong1，DAI Yin-mei2，ZHANG Jia-jin1，ZHANG Zhuo-yong1* |
1. Department of Chemistry，Capital Normal University，Beijing 100048，China
2. Beijing Obstetrics and Gynecology Hospital，Capital Medical University，Beijing 100006，China |
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Abstract Near-infrared spectroscopy combined with chemometrics methods for diagnosis of cancer has been reported in literatures. In our study, the NIR spectra of 77 specimens of different physiological stages of endometrium were collected. Spectral data were pretreated firstly by multiplicative scatter correction (MSC), orthogonal signal correction (OSC), and both of them, respectively, and then by SG smoothing. Latin partition method was used to select 3/4 samples as a training set, and the other 1/4 samples for test set. Support vector machine (SVM) model was built for classification, and the classification results was compared with that of partial least squares (PLS) model based on the same pretreatment methods. Samples of malignant, hyperplasia and normal endometrium were classified better by SVM (classification accuracy was 92%) than PLS (classification accuracy was 90%). The results suggested that classification accuracy was affected by pretreatment methods and models. SVM combined with endometrial tissue near infrared spectroscopy is expected to develop into a new approach to tumor diagnosis.
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Received: 2010-06-18
Accepted: 2010-09-22
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Corresponding Authors:
ZHANG Zhuo-yong
E-mail: gusto2008@vip.sina.com
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