EventsMOL2NET'22, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 8th ed.
Event submissions
Published
with-doi10.3390/mol2net-08-13911
This submission belongs to the session 01. CHEMBIO.INFO-08: Cheminfo., Chemom., Comput. Chem. & Bioinfo., Congress München, GR-Cambridge, UK-Ch. Hill, USA, 2022. of the event MOL2NET'22, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 8th ed.
Published date
26 Dec, 2022
Academic Editor
author-avatarHumbert G. Díaz
Citation
Andrea Ruiz Escudero, The application of Machine Learning to Raman spectroscopy, in Proceedings of MOL2NET'22, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 8th ed., 1 January–15 January 2023, MDPI: Basel, Switzerland, doi: 10.3390/mol2net-08-13911
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The application of Machine Learning to Raman spectroscopy

Andrea Ruiz Escudero 1,2
1. Department of Pharmacology, Faculty of Medicine and Nursing, University of the Basque Country (UPV/EHU), Leioa, Biscay, Spain.
2. Department of Information and Communication Technologies, Computer Science Faculty, University of A Coruña,Campus de Elviña, A Coruña, Spain.
Abstract

In analytical science, data extraction from complex or extensive datasets can be a laborious task that takes a long time to complete. Machine learning (ML) offers a pioneering opportunity to rapidly extract information from chromatography, spectroscopy, and mass spectrometry datasets, among others. Over the past few years, new approaches have been developed for the rapid processing of Raman spectra using ML. This review will discuss different applications of ML techniques employed in Raman.

Keywords
machine learning
analytical science
Raman
Manuscript
The application of Machine Learning to Raman spectroscopy.pdf
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