Automated assessment of skin histological tissue structures by artificial intelligence in cutaneous melanoma.

Journal: Pathology, research and practice
PMID: 40158269

Abstract

BACKGROUND: Prognostic histopathological features such as mitosis in melanoma are excluded from the staging systems due to inter-observer variability and time constraints. While digital pathology offers artificial intelligence-driven solutions, existing melanoma algorithms often underperform or narrowly focus on specific features, limiting their clinical utility.

Authors

  • Thamila Kerkour
    Department of Dermatology, Erasmus MC, Rotterdam, the Netherlands.
  • Loes Hollestein
    Department of Dermatology, Erasmus MC, Rotterdam, the Netherlands.
  • Alex Nigg
    Department of Pathology, Erasmus MC, Rotterdam, the Netherlands.
  • Sjors A Koppes
    Department of Pathology, Erasmus MC, Rotterdam, the Netherlands.
  • Tamar Nijsten
    Department of Dermatology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Rotterdam, 3015 GD, The Netherlands.
  • Yunlei Li
    Department of Pathology and Clinical Bioinformatics, Erasmus University Medical Center, Rotterdam, The Netherlands.
  • Antien Mooyaart
    Department of Pathology, Erasmus MC, Rotterdam, the Netherlands. Electronic address: a.mooyaart@erasmusmc.nl.

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