Melanoma Recognition Using Negative Selection
Melanoma is the deadliest form of skin cancer and the most dangerous type. It is curable if detected earlier. The problem occurred when the current diagnosis biopsy method consumed much time and pain. Based on the proposed technique, the image of melanoma will be used. Corresponding features will be...
Published in: | 2023 4th International Conference on Artificial Intelligence and Data Sciences: Discovering Technological Advancement in Artificial Intelligence and Data Science, AiDAS 2023 - Proceedings |
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2-s2.0-85176615148 Ruslan M.R.H.; Sa'dan S.; Bahrin U.F.M.; Hamzah S.S.; Yasin S.N.S.; Ishak S.N.H. Melanoma Recognition Using Negative Selection 2023 2023 4th International Conference on Artificial Intelligence and Data Sciences: Discovering Technological Advancement in Artificial Intelligence and Data Science, AiDAS 2023 - Proceedings 10.1109/AiDAS60501.2023.10284661 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85176615148&doi=10.1109%2fAiDAS60501.2023.10284661&partnerID=40&md5=0bc15d35c90787b82d2b786dbf1184c3 Melanoma is the deadliest form of skin cancer and the most dangerous type. It is curable if detected earlier. The problem occurred when the current diagnosis biopsy method consumed much time and pain. Based on the proposed technique, the image of melanoma will be used. Corresponding features will be extracted based on the asymmetry, border, colour, and diameter (ABCD) rule of dermoscopy with Negative Selection Algorithm to classify melanoma skin cancer and benign mole. The accuracy of the proposed technique is 60%, specificity gained 75%, and sensitivity of 50% was recorded for the algorithm evaluation. © 2023 IEEE. Institute of Electrical and Electronics Engineers Inc. English Conference paper |
author |
Ruslan M.R.H.; Sa'dan S.; Bahrin U.F.M.; Hamzah S.S.; Yasin S.N.S.; Ishak S.N.H. |
spellingShingle |
Ruslan M.R.H.; Sa'dan S.; Bahrin U.F.M.; Hamzah S.S.; Yasin S.N.S.; Ishak S.N.H. Melanoma Recognition Using Negative Selection |
author_facet |
Ruslan M.R.H.; Sa'dan S.; Bahrin U.F.M.; Hamzah S.S.; Yasin S.N.S.; Ishak S.N.H. |
author_sort |
Ruslan M.R.H.; Sa'dan S.; Bahrin U.F.M.; Hamzah S.S.; Yasin S.N.S.; Ishak S.N.H. |
title |
Melanoma Recognition Using Negative Selection |
title_short |
Melanoma Recognition Using Negative Selection |
title_full |
Melanoma Recognition Using Negative Selection |
title_fullStr |
Melanoma Recognition Using Negative Selection |
title_full_unstemmed |
Melanoma Recognition Using Negative Selection |
title_sort |
Melanoma Recognition Using Negative Selection |
publishDate |
2023 |
container_title |
2023 4th International Conference on Artificial Intelligence and Data Sciences: Discovering Technological Advancement in Artificial Intelligence and Data Science, AiDAS 2023 - Proceedings |
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doi_str_mv |
10.1109/AiDAS60501.2023.10284661 |
url |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85176615148&doi=10.1109%2fAiDAS60501.2023.10284661&partnerID=40&md5=0bc15d35c90787b82d2b786dbf1184c3 |
description |
Melanoma is the deadliest form of skin cancer and the most dangerous type. It is curable if detected earlier. The problem occurred when the current diagnosis biopsy method consumed much time and pain. Based on the proposed technique, the image of melanoma will be used. Corresponding features will be extracted based on the asymmetry, border, colour, and diameter (ABCD) rule of dermoscopy with Negative Selection Algorithm to classify melanoma skin cancer and benign mole. The accuracy of the proposed technique is 60%, specificity gained 75%, and sensitivity of 50% was recorded for the algorithm evaluation. © 2023 IEEE. |
publisher |
Institute of Electrical and Electronics Engineers Inc. |
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language |
English |
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Conference paper |
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scopus |
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Scopus |
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1809677889751220224 |