The paper performs results of the use of machine learning methods to differentiate SERS spectra in patients with and without cardiovascular pathologies. Approaches were applied to processing spectral data arrays consisting of 1266 spectra for various groups of patients: healthy patients, patients with pathology of cardiovascular diseases, healthy patients receiving therapy, and patients with pathology of cardiovascular diseases receiving therapy. The applicability of the random forest algorithm for classification problems were shown. Potential spectral biomarkers of differences between the groups of patients on whom these algorithms were tested were identified. The achieved classification accuracy using the random forest spectra algorithm for the groups of healthy patients without therapy and patients with cardiovascular pathology without therapy was 83.4%. When classifying the presence of therapy in healthy patients (control), the accuracy was 76.26%; in patients with cardiovascular pathology, the accuracy was 70%.
This paper performs detailed study of Raman scattering for platelets mixed with gold nanoparticles in presence with R6G molecules on quartz surface. Spectral properties of main spectral bands corresponding to proteins and dye in the complexes with gold nanoparticles have been performed. The perspectives SERS for applications in modern physics and biophotonics have been shown. Results of the study can be applied for SERS detection and investigation of blood components such as cells and platelets. Paper describes characteristic maxima of different cell components and its identification in platelets.
This paper describes detailed study of single human platelet and can be used for rapid and early structure changes and biomarkers identification in individuals with cardiovascular decease (CCD) pathology in vitro. The obtained data include analyzed Surface-enhanced Raman spectra (SERS) of human platelets taken from healthy individuals and individuals with cardiovascular pathology. Paper describes characteristic maxima of different cell components and its changes in platelets.
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