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Discrimination of vocal folds lesions by multiclass classification using autofluorescence spectroscopy: An ex vivo study.

Olivier GaiffeJoackim MahdjoubEmmanuel RamassoOlivier MauvaisThomas LihoreauLionel PazartBruno WacogneLaurent Tavernier
Published in: Head & neck (2024)
The ex vivo study demonstrates the effectiveness of AFS combined with multivariate analysis for accurate classification of vocal fold lesions. Comprehensive analysis of spectral data significantly improves classification accuracy, such as distinguishing malignant from precancerous or benign lesions.
Keyphrases
  • machine learning
  • deep learning
  • high resolution
  • systematic review
  • mass spectrometry
  • big data
  • electronic health record
  • computed tomography
  • artificial intelligence
  • single molecule