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Siqueira, L.F.S., Júnior, R.F.A., Araújo, A.A.D., et al. (2017) LDA vs. QDA for FT-MIR Prostate Cancer Tissue Classification. Chemometrics & Intelligent Laboratory Systems, 162, 123-129.
https://doi.org/10.1016/j.chemolab.2017.01.021

has been cited by the following article:

• TITLE: Pattern Recognition Methods Combined with Raman Spectra Applied to Distinguish Serums from Lung Cancer Patients and Healthy People

  AUTHORS: Yankun Li, Mingjing Jia, Xiangchao Zeng, Kenan Huang, Zhichao Bai

  KEYWORDS: Raman Spectroscopy, Pattern Recognition, Lung Cancer Identification, Serum

  JOURNAL NAME: Journal of Biosciences and Medicines, Vol.5 No.9, September 20, 2017

  ABSTRACT: Raman spectroscopy was used to distinguish the serums from lung cancer patients and healthy people, through spectral pretreatment method combined with pattern recognition methods including principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA), un-correlated linear discriminant analysis (ULDA), etc. Through the comparisons of the results, it can be found that ULDA and LDA combined with multiple scatter correction (MSC) pretreatment method successfully distinguish the patients of lung cancer and healthy people. The method has academic significance and promising clinical application value.