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Genetic algorithm spectral feature selection coupled with quadratic discriminant analysis for ATR-FTIR spectrometric diagnosis of basal cell carcinoma via blood sample analysis

机译:遗传算法光谱特征选择和二次判别分析通过血样分析对基底细胞癌进行ATR-FTIR光谱诊断

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摘要

A diagnostic approach for basal cell carcinoma (BCC) has been developed based on investigation of the infrared spectra of blood samples. Different predictive procedures were developed using quadratic discriminant analysis (QDA) combined with a simple filtered method and genetic algorithm (GA) as a feature subset and wavelength selection strategy. Results showed 94.74% and 100% accuracy for Filtering-QDA and GA-QDA models, respectively.
机译:基于对血液样本红外光谱的研究,已经开发出一种诊断基底细胞癌(BCC)的方法。使用二次判别分析(QDA)结合简单的滤波方法和遗传算法(GA)作为特征子集和波长选择策略,开发了不同的预测程序。结果显示Filtering-QDA模型和GA-QDA模型的准确度分别为94.74%和100%。

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