Correction: An effective multiclass skin cancer classification approach based on deep convolutional neural network
1 0 0 7 / s 1 0 5 8 6 -0 2 4 -0 4 5 4 0 -1In this article under the section heading '5.1 Performance metrics' the word 'six' has been incorrectly written as 'sex' in the following sentence: "The performance of the proposed DCNN model was evaluated using sex evaluation metrics including accuracy, recall, precision, F1-score, specificity, and AUC.The incorporation of these metrics provided a nuanced under standing of the DCNN's performance across different facets, ensuring a comprehensive evaluation of its effectiveness in skin cancer classification''.
Authors
- Essam Halim Houssein (ORCID: https://orcid.org/0000-0002-8127-7233)
- Doaa A. Abdelkareem (ORCID: https://orcid.org/0000-0002-1441-1981)
- Mohamed Abdel Hameed (ORCID: https://orcid.org/0000-0002-2911-770X)
- M. Y. A. Younan
- Gang Hu
- Ibrahim A. Ibrahim
Institutions
- Xi'an University of Technology (CN)
- Minia University (EG)
Publication Details
- Journal
- Cluster Computing
- Published
- 2026-03-26
- DOI
- https://doi.org/10.1007/s10586-026-06099-5
- Primary Topic
- Cutaneous Melanoma Detection and Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00