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

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.