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首页> 外文期刊>Photodiagnosis and Photodynamic Therapy >Diagnosis of cervical squamous cell carcinoma and cervical adenocarcinoma based on Raman spectroscopy and support vector machine
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Diagnosis of cervical squamous cell carcinoma and cervical adenocarcinoma based on Raman spectroscopy and support vector machine

机译：基于拉曼光谱和支持向量机的宫颈鳞癌和宫颈腺癌诊断

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In this report, we collected the Raman spectrum of cervical adenocarcinoma and cervical squamous cell carcinoma tissues by a micro-Raman spectroscopy system. We analysed, compared and summarized the characteristics and differences of the normalized mean Raman spectra of the two tissues and pointed out the major differences in the biochemical composition between the two tissues. The PCA-SVM model that was used to distinguish the two types of cervical cancer tissues was established. The accuracy of the model in differentiating cervical adenocarcinoma from cervical squamous cell carcinoma was 93.125%.The results of this study indicate that Raman spectroscopy of cervical adenocarcinoma and cervical squamous cell carcinoma tissue in combination with SVM (support vector analysis) and PCA (principal component analysis) can be useful for the classification of cervical adenocarcinoma and cervical squamous cell carcinoma tissues and for the exploration of the differences in biochemical compositions between the two types of cervical tissue. This study lays a foundation to further study Raman spectroscopy as a clinical diagnostic method for cervical cancer.
机译：在本报告中，我们通过微拉曼光谱系统收集了宫颈腺癌和宫颈鳞状细胞癌组织的拉曼光谱。我们分析，比较和总结了两种组织的归一化平均拉曼光谱的特征和差异，并指出了两种组织之间生化成分的主要差异。建立了用于区分两种宫颈癌组织的PCA-SVM模型。该模型区分宫颈腺癌和宫颈鳞状细胞癌的准确性为93.125％。研究结果表明，宫颈腺癌和宫颈鳞状细胞癌组织的拉曼光谱结合SVM（支持向量分析）和PCA（主要成分）分析）可用于宫颈腺癌和宫颈鳞状细胞癌组织的分类以及探索两种类型宫颈组织之间生化成分的差异。该研究为进一步研究拉曼光谱法作为宫颈癌的临床诊断方法奠定了基础。

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