Diagnosis with confidence: deep learning for reliable classification of laryngeal dysplasia.

Journal: Histopathology
PMID: 37872676

Abstract

BACKGROUND: Diagnosis of head and neck (HN) squamous dysplasias and carcinomas is critical for patient care, cure, and follow-up. It can be challenging, especially for grading intraepithelial lesions. Despite recent simplification in the last WHO grading system, the inter- and intraobserver variability remains substantial, particularly for nonspecialized pathologists, exhibiting the need for new tools to support pathologists.

Authors

  • Mélanie Lubrano
    Centre for Computational Biology (CBIO), Mines Paris, PSL University, Paris, France.
  • Yaëlle Bellahsen-Harrar
    Department of Pathology, APHP, Hôpital Européen Georges-Pompidou, Paris, France.
  • Sylvain Berlemont
    Keen Eye, Paris, France.
  • Sarah Atallah
    Sorbonne Université, Paris, France.
  • Emmanuelle Vaz
    Department of Pathology, Hôpital Tenon, Paris, France.
  • Thomas Walter
  • Cécile Badoual
    Department of Pathology, APHP, Hôpital Européen Georges-Pompidou, Paris, France.

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