Computational Assessment of Spectral Heterogeneity within Fresh Glioblastoma Tissue Using Raman Spectroscopy and Machine Learning Algorithms

Computational Assessment of Spectral Heterogeneity within Fresh Glioblastoma Tissue Using Raman Spectroscopy and Machine Learning Algorithms

Understanding and classifying inherent tumor heterogeneity is a multimodal approach, which can be undertaken at the genetic, biochemical, or morphological level, among others. Optical spectral methods such as Raman spectroscopy aim at rapid and non-destructive tissue analysis, where each spectrum ge...

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Bibliographic Details
Main Authors: Karoline Klein, Gilbert Georg Klamminger, Laurent Mombaerts, Finn Jelke, Isabel Fernandes Arroteia, Rédouane Slimani, Giulia Mirizzi, Andreas Husch, Katrin B. M. Frauenknecht, Michel Mittelbronn, Frank Hertel, Felix B. Kleine Borgmann
Format: Article
Language:English
Published: MDPI AG 2024-02-01
Series:Molecules
Subjects:
Raman spectroscopy
vibrational spectroscopy
glioblastoma
brain tumor
heterogeneity
machine learning
Online Access:https://www.mdpi.com/1420-3049/29/5/979

Internet

https://www.mdpi.com/1420-3049/29/5/979

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