Scientists identify brain tumors using blood samples TomskUni
]. The same patterns are seen in the most informative Raman spectral features for each stage of the experiment. Thus, we show that the analysis of blood serum can track the change in the state of brain tissues during the development of glioblastoma.
The presented results confirm the possibility of glioblastoma detection by Raman spectra analysis of blood serum. This study has several limitations. First of all, the number of samples in each group is not large . Though a proper validation of constructed machine learning models is made, a comparison to a reference method is required, namely, MRS, to determine metabolites in tumor and blood tests in order to find the quantity of these metabolites in blood.
The strong sides of this study are the following. The conducted experiments with a small animal glioblastoma model were performed in strict accordance with the research protocol and can be reproduced. State-of-the-art machine learning methods were used to verify the separability of the classes for each week of the experiment. The validity of the obtained results is tested by k-fold CV techniques and ROC AUC analysis.
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