Nature Communications (Oct 2019)

Rapid identification of pathogenic bacteria using Raman spectroscopy and deep learning

  • Chi-Sing Ho,
  • Neal Jean,
  • Catherine A. Hogan,
  • Lena Blackmon,
  • Stefanie S. Jeffrey,
  • Mark Holodniy,
  • Niaz Banaei,
  • Amr A. E. Saleh,
  • Stefano Ermon,
  • Jennifer Dionne

DOI
https://doi.org/10.1038/s41467-019-12898-9
Journal volume & issue
Vol. 10, no. 1
pp. 1 – 8

Abstract

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The use of Raman spectroscopy for pathogen identification is hampered by the weak Raman signal and phenotypic diversity of bacterial cells. Here the authors generate an extensive dataset of bacterial Raman spectra and apply deep learning to identify common bacterial pathogens and predict antibiotic treatment from noisy Raman spectra.