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基于逻辑回归和近红外光谱的子宫内膜癌诊断

[Diagnosis of endometrial cancer based on logistic regression and near infrared spectroscopy].

作者信息

Zhang Jia-Jin, Zhang Zhuo-Yong, Xiang Yu-Hong, Yang Fan

机构信息

Department of Chemistry, Capital Normal University, Beijing 100048, China.

出版信息

Guang Pu Xue Yu Guang Pu Fen Xi. 2013 Feb;33(2):344-8.

Abstract

Endometrial carcinoma is one of the most common gynecologic cancers. The present paper reports a new application of Logistic regression to building model of endometrial cancer. Near infrared (NIR) spectra was introduced. In our study, the NIR spectra of 77 specimens were pretreated by principal component-linear discriminant analysis (PC-LDA) and support vector machine discriminant analysis (SVM-DA). Latin partition method for selecting training and test sets was used to determine the significant parameters for Logistic regression model. From the predicted results of logistic regression model, both the categories of samples and the trends of samples belonging to other class were clear and concordant with the clinical result. The proposed procedure proved to be suitable to being developed as a noninvasive diagnosis method for cancer tissue.

摘要

子宫内膜癌是最常见的妇科癌症之一。本文报道了逻辑回归在构建子宫内膜癌模型中的一种新应用。引入了近红外(NIR)光谱。在我们的研究中,77个样本的近红外光谱通过主成分-线性判别分析(PC-LDA)和支持向量机判别分析(SVM-DA)进行了预处理。采用拉丁划分法选择训练集和测试集来确定逻辑回归模型的显著参数。从逻辑回归模型的预测结果来看,样本类别以及属于其他类别的样本趋势都很清晰,且与临床结果一致。所提出的方法被证明适合开发成为一种癌症组织的非侵入性诊断方法。

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