title: Surface-enhanced Raman spectroscopy + support vector machine: a new noninvasive method for prostate cancer screening?
abstract: Prostate cancer is one of the most common malignancies of the older males worldwide. Early diagnosis and treatment are important to improve the survival of patients. Recently, we developed a new method for prostate cancer screening: by measuring the serum surface-enhanced Raman spectroscopy of prostate cancer patients and normal subjects, combining with classification algorithms of support vector machines, the measured surface-enhanced Raman spectroscopy spectra are successfully classified with accuracy of 98.1%. Although the practical application faces several difficulties, we believe that this label-free serum surface-enhanced Raman spectroscopy analysis technique combined with support vector machine diagnostic algorithms will become a powerful tool for noninvasive prostate cancer screening in the future.
authors.affiliation: Biomedical Engineering Laboratory, Guangdong Medical College, Dongguan 523808, China.
authors.forename: Shaoxin
authors.initials: S
authors.lastname: Li
authors.forename: Zhouyi
authors.initials: Z
authors.lastname: Guo
authors.forename: Zhiming
authors.initials: Z
authors.lastname: Liu
mesh_terms: D006801:Humans; D008297:Male; D008403:Mass Screening / Q000379:methods; D011237:Predictive Value of Tests; D011471:Prostatic Neoplasms / Q000175:diagnosis*; D013059:Spectrum Analysis, Raman / Q000379:methods*; D060388:Support Vector Machine
keywords: classification; prostate cancer; serum; support vector machine; surface enhanced Raman spectroscopy