论文标题
恶性肿瘤细胞与人类正常白细胞之间的内在特征，并通过拉曼光谱法分析统计决策树分析
Intrinsic feature between malignant tumor cells and human normal leukocytes with statistical decision tree analysis via Raman spectroscopy
论文作者
论文摘要
在这项研究中，提出了一种开发的数据挖掘技术的组合，称为统计决策树分析方法和拉曼光谱法，以区分人类正常白细胞与恶性肿瘤细胞。获得的统计结果表明，该方法具有令人钦佩的表现，一方面，平均分类精度为94.43％，基础腺嘌呤和酰胺I被认为是对主要和亚构中生物学差异的潜在特征。此外，这些反映固有生理差异的某些拉曼带可以从整个指纹光谱中方向提取，然后为光谱识别提供快速准确的操纵。
In this study, the combination of a developing data mining technique called statistical decision tree analysis method and Raman spectroscopy was proposed to differentiate human normal leukocytes from malignant tumor cells. Statistical results obtained indicate this method possesses an admirable performance of a mean classification accuracy of 94.43% on the one hand, base adenine and amide I are recognized as potential characterizations of main- and subintrinsic biological difference in between on the other hand. Moreover, these certain Raman bands reflecting intrinsic physiological differences can be directionally extracted from whole fingerprint spectra and then provide a fast and accurate manipulation for spectrum identification.
