Surface-enhanced Raman spectroscopy (SERS) datasets obtained from biomedical samples are rich in information, but this wealth of information is not always easy to get. Extracting the right information from this complexity is a challenging task. Preprocessing procedures and multivariate analysis methods are extremely powerful tools to help us in this task. These tools, however, are as powerful as dangerous, if not correctly used, and can easily lead to wrong conclusions. This chapter is a short introduction into the analysis and interpretation of SERS spectral data in biomedical studies. The aim is to give practical advices to the researcher through a quick overview of the most relevant techniques for data visualization and analysis, with an emphasis on both their capabilities and weaknesses.

Data analysis in SERS diagnostics

Fornasaro, Stefano;Beleites, Claudia;Sergo, Valter;Bonifacio, Alois
2022

Abstract

Surface-enhanced Raman spectroscopy (SERS) datasets obtained from biomedical samples are rich in information, but this wealth of information is not always easy to get. Extracting the right information from this complexity is a challenging task. Preprocessing procedures and multivariate analysis methods are extremely powerful tools to help us in this task. These tools, however, are as powerful as dangerous, if not correctly used, and can easily lead to wrong conclusions. This chapter is a short introduction into the analysis and interpretation of SERS spectral data in biomedical studies. The aim is to give practical advices to the researcher through a quick overview of the most relevant techniques for data visualization and analysis, with an emphasis on both their capabilities and weaknesses.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/3028565
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