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Vol. 33 No. 69 (2024)
July-September 2024: Open Science at the Service of Engineering

Papers

Explainable Classification of Dermoscopy Images for the Detection of Melanoma: A Systematic Mapping of the Literature

https://doi.org/10.19053/uptc.01211129.v33.n69.2024.18060

Published 2024-09-30

  • Iván-Santiago Herrera-Bravo
    • ,
  • Hugo-Armando Ordoñez-Erazo
    • ,
  • Himer Avila-George

Iván-Santiago Herrera-Bravo
University of Cauca image/svg+xml

Hugo-Armando Ordoñez-Erazo
University of Cauca image/svg+xml

Himer Avila-George
University of Guadalajara image/svg+xml

Abstract

Recently, artificial intelligence models applied to the detection of melanoma have shown promising results. However, the adoption of these technologies is hampered by a lack of transparency in automatic decision-making. To address this problem, Explainable Artificial Intelligence (XAI) is emerging, which seeks to reduce gaps by providing mechanisms to understand why a system makes a specific decision. Therefore, this systematic mapping examines how XAI has evolved in the detection of melanoma skin cancer. As a result, sixteen scientific articles that strictly applied explainability methods to melanoma classification models were identified. Finally, the incidence of melanoma in Colombia was determined.

Keywords

Explainable artificial intelligence (XAI), Melanoma, Classification, Dermatoscopic images

PDF (Español)

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