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2 December 2021 Informative feature selection method for Raman micro-spectroscopy data
A. V. Karmenyan, D. A. Vrazhnov Sr., E. A. Sandykova, E. V. Perevedentseva, A. S. Krivokharchenko, V. A. Nadtochenko, C.-L. Cheng, T. V. Kabanova, T. E. Malakhova
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Proceedings Volume 12086, XV International Conference on Pulsed Lasers and Laser Applications; 120861H (2021) https://doi.org/10.1117/12.2613966
Event: XV International Conference on Pulsed Lasers and Laser Applications, 2021, Tomsk, Russian Federation
Abstract
The paper presents an algorithm based on low order statistics for the informative feature extraction for Raman spectroscopy data. The proposed method was tested on mouse preimplantation embryos Raman spectra. Both supervised and unsupervised machine learning methods were applied to selected the most informative features to test the separability of the processed data.
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A. V. Karmenyan, D. A. Vrazhnov Sr., E. A. Sandykova, E. V. Perevedentseva, A. S. Krivokharchenko, V. A. Nadtochenko, C.-L. Cheng, T. V. Kabanova, and T. E. Malakhova "Informative feature selection method for Raman micro-spectroscopy data", Proc. SPIE 12086, XV International Conference on Pulsed Lasers and Laser Applications, 120861H (2 December 2021); https://doi.org/10.1117/12.2613966
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KEYWORDS
Raman spectroscopy
Feature selection
Machine learning
Statistical analysis
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