Glioma <i>biopsies</i> Classification Using Raman Spectroscopy and Machine Learning Models on Fresh Tissue Samples

Glioma <i>biopsies</i> Classification Using Raman Spectroscopy and Machine Learning Models on Fresh Tissue Samples

Identifying tumor cells infiltrating normal-appearing brain tissue is critical to achieve a total glioma resection. Raman spectroscopy (RS) is an optical technique with potential for real-time glioma detection. Most RS reports are based on formalin-fixed or frozen samples, with only a few studies de...

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Bibliographic Details
Main Authors: Marco Riva, Tommaso Sciortino, Riccardo Secoli, Ester D’Amico, Sara Moccia, Bethania Fernandes, Marco Conti Nibali, Lorenzo Gay, Marco Rossi, Elena De Momi, Lorenzo Bello
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Cancers
Subjects:
Raman spectroscopy
neuro-oncology
classification
glioma
machine learning
Online Access:https://www.mdpi.com/2072-6694/13/5/1073

Internet

https://www.mdpi.com/2072-6694/13/5/1073

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