Mathematical Analysis of Raman Spectra Data Arrays Using Machine Learning Algorithms

This paper is devoted to the application of mathematical methods classification and differentiation low-resolution spectral data arrays Raman light scattering for complex biological compounds as human platelets. Spectral consisted 1266 spectra from 4 groups patients, totaling 152 people were analyzed. A random forest algorithm was used. Potential biomarkers differences between patient identified, on which given algorithms tested. Using healthy patients without therapy with cardiovascular pathologies therapy, we have achieved accuracy 83.4%. Classification off shows 76.26% 70% accuracy.