Comparison of the performance of linear multivariate analysis methods for normal and dyplasia tissues differentiation using autofluorescence spectroscopy

Chia Chu Shou, Tzu Chien Ryan Hsiao, Jen K. Lin, Chih Yu Wang, Kenny Chiang Huihua*

*此作品的通信作者

研究成果: Article同行評審

21 引文 斯高帕斯(Scopus)

摘要

We compared the performance of three widely used linear multivariate methods for autofluorescence spectroscopic tissues differentiation. Principal component analysis (PCA), partial least squares (PLS), and multivariate linear regression (MVLR) were compared for differentiating at normal, tubular adenoma/epithelial dysplasia and cancer in colorectal and oral tissues. The methods' performances were evaluated by cross-validation analysis. The group-averaged predictive diagnostic accuracies were 85% (PCA), 90% (PLS), and 89% (MVLR) for colorectal tissues; 89% (PCA), 90% (PLS), and 90% (MVLR) for oral tissues. This study found that both PLS and MVLR achieved higher diagnostic results than did PCA.

原文English
頁(從 - 到)2265-2273
頁數9
期刊IEEE Transactions on Biomedical Engineering
53
發行號11
DOIs
出版狀態Published - 1 11月 2006

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