Raman microspectroscopy and machine learning for use in identifying radiation-induced lung toxicity.

Journal: PloS one
Published Date: Dec 30, 2022

Abstract

OBJECTIVE: In this work, we explore and develop a method that uses Raman spectroscopy to measure and differentiate radiation induced toxicity in murine lungs with the goal of setting the foundation for a predictive disease model.

Authors

  • Ramie N Ali-Adeeb
    Department of Physics, The University of British Columbia - Okanagan campus, Kelowna, BC, Canada.
  • Phil Shreeves
    Department of Statistics, The University of British Columbia - Okanagan campus, Kelowna, BC, Canada.
  • Xinchen Deng
    Department of Physics, The University of British Columbia - Okanagan campus, Kelowna, BC, Canada.
  • Kirsty Milligan
    Department of Physics, The University of British Columbia - Okanagan campus, Kelowna, BC, Canada.
  • Alex G Brolo
    Department of Chemistry, University of Victoria, Victoria, BC, Canada.
  • Jullian J Lum
    Department of Biochemistry and Microbiology, University of Victoria, Victoria, BC, Canada.
  • Christina Haston
    Department of Physics, The University of British Columbia - Okanagan campus, Kelowna, BC, Canada.
  • Jeffrey L Andrews
    Department of Statistics, The University of British Columbia - Okanagan campus, Kelowna, BC, Canada.
  • Andrew Jirasek
    Department of Physics, The University of British Columbia - Okanagan campus, Kelowna, BC, Canada.

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