Skin Cancer Detection Using Deep Learning—A Review
Skin cancer is one the most dangerous types of cancer and is one of the primary causes of death worldwide. The number of deaths can be reduced if skin cancer is diagnosed early. Skin cancer is mostly diagnosed using visual inspection, which is less accurate. Deep-learning-based methods have been pro...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-05-01
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| Series: | Diagnostics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-4418/13/11/1911 |
| _version_ | 1797597717816410112 |
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| author | Maryam Naqvi Syed Qasim Gilani Tehreem Syed Oge Marques Hee-Cheol Kim |
| author_facet | Maryam Naqvi Syed Qasim Gilani Tehreem Syed Oge Marques Hee-Cheol Kim |
| author_sort | Maryam Naqvi |
| collection | DOAJ |
| description | Skin cancer is one the most dangerous types of cancer and is one of the primary causes of death worldwide. The number of deaths can be reduced if skin cancer is diagnosed early. Skin cancer is mostly diagnosed using visual inspection, which is less accurate. Deep-learning-based methods have been proposed to assist dermatologists in the early and accurate diagnosis of skin cancers. This survey reviewed the most recent research articles on skin cancer classification using deep learning methods. We also provided an overview of the most common deep-learning models and datasets used for skin cancer classification. |
| first_indexed | 2024-03-11T03:09:26Z |
| format | Article |
| id | doaj.art-4bc9bba629654da6b2fafbdff0f0f3af |
| institution | Directory Open Access Journal |
| issn | 2075-4418 |
| language | English |
| last_indexed | 2024-03-11T03:09:26Z |
| publishDate | 2023-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Diagnostics |
| spelling | doaj.art-4bc9bba629654da6b2fafbdff0f0f3af2023-11-18T07:42:46ZengMDPI AGDiagnostics2075-44182023-05-011311191110.3390/diagnostics13111911Skin Cancer Detection Using Deep Learning—A ReviewMaryam Naqvi0Syed Qasim Gilani1Tehreem Syed2Oge Marques3Hee-Cheol Kim4Institute of Digital Anti-Aging Healthcare, Inje University, Gimhae 50834, Republic of KoreaDepartment of Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL 33431, USADepartment of Electrical Engineering and Computer Engineering, Technische Universität Dresden, 01069 Dresden, GermanyDepartment of Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL 33431, USAInstitute of Digital Anti-Aging Healthcare, Inje University, Gimhae 50834, Republic of KoreaSkin cancer is one the most dangerous types of cancer and is one of the primary causes of death worldwide. The number of deaths can be reduced if skin cancer is diagnosed early. Skin cancer is mostly diagnosed using visual inspection, which is less accurate. Deep-learning-based methods have been proposed to assist dermatologists in the early and accurate diagnosis of skin cancers. This survey reviewed the most recent research articles on skin cancer classification using deep learning methods. We also provided an overview of the most common deep-learning models and datasets used for skin cancer classification.https://www.mdpi.com/2075-4418/13/11/1911skin cancersegmentationclassificationdeep learning |
| spellingShingle | Maryam Naqvi Syed Qasim Gilani Tehreem Syed Oge Marques Hee-Cheol Kim Skin Cancer Detection Using Deep Learning—A Review Diagnostics skin cancer segmentation classification deep learning |
| title | Skin Cancer Detection Using Deep Learning—A Review |
| title_full | Skin Cancer Detection Using Deep Learning—A Review |
| title_fullStr | Skin Cancer Detection Using Deep Learning—A Review |
| title_full_unstemmed | Skin Cancer Detection Using Deep Learning—A Review |
| title_short | Skin Cancer Detection Using Deep Learning—A Review |
| title_sort | skin cancer detection using deep learning a review |
| topic | skin cancer segmentation classification deep learning |
| url | https://www.mdpi.com/2075-4418/13/11/1911 |
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