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''.

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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
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article

Correction: An effective multiclass skin cancer classification approach based on deep convolutional neural network

Essam Halim Houssein, Doaa A. Abdelkareem, Mohamed Abdel Hameed, M. Y. A. Younan et al.
Cluster Computing
Cutaneous Melanoma Detection and Management
article

Correction: An effective multiclass skin cancer classification approach based on deep convolutional neural network

Essam Halim Houssein, Doaa A. Abdelkareem, Mohamed Abdel Hameed, M. Y. A. Younan, Gang Hu, Ibrahim A. Ibrahim
article en

Abstract

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''.

Cluster ComputingVol. 29(3)
Xi'an University of Technology (CN), Minia University (EG)
Openalex Percentile: Top 7%
Cutaneous Melanoma Detection and Management
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