Stratification of tumour cell radiation response and metabolic signatures visualization with Raman spectroscopy and explainable convolutional neural network

Author:

Fuentes Alejandra M.1ORCID,Milligan Kirsty1ORCID,Wiebe Mitchell1ORCID,Narayan Apurva23,Lum Julian J.45,Brolo Alexandre G.6ORCID,Andrews Jeffrey L.7,Jirasek Andrew1

Affiliation:

1. Department of Physics, The University of British Columbia Okanagan Campus, Kelowna, Canada

2. Department of Computer Science, Western University, London, Canada

3. Department of Computer Science, The University of British Columbia Okanagan Campus, Kelowna, Canada

4. Department of Biochemistry and Microbiology, The University of Victoria, Victoria, Canada

5. Trev and Joyce Deeley Research Centre, BC Cancer, Victoria, Canada

6. Department of Chemistry, The University of Victoria, Victoria, Canada

7. Department of Statistics, The University of British Columbia Okanagan Campus, Kelowna, Canada

Abstract

A CNN was developed for classifying Raman spectra of radiosensitive and radioresistant tumour cells. Furthermore, a CNN explainability method was proposed to identify biomolecular Raman signatures associated with the observed radiation responses.

Funder

Natural Sciences and Engineering Research Council of Canada

Canadian Institutes of Health Research

Publisher

Royal Society of Chemistry (RSC)

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