Abstract
We report a label-free Surface Enhanced Raman Spectroscopy (SERS) for pleural fluid analysis to distinguish Lung cancer from controls patients. Herein, we have used a novel silver coated silicon Nanopillar (SCSNP) as SERS substrate to acquire multiple SERS spectra for each pleural fluid sample and advanced chemometrics methods. We report a classification accuracy of 85% along with sensitivity and specificity of 87% and 83% respectively for the detection of Lung cancer over control pleural fluid samples with a receiver operating characteristics (ROC) area under curve value of 0.92 using PLS-DA binary classifier to distinguish between lung cancer over control subjects.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
