Skin cancer diagnostics: a VGGEnsemble approach
The human skin is the largest organ of the human body, and it is highly susceptible to lesions. This study attempts to classify two distinct classes of malignant skin cancers, i.e., Actinic Keratosis (AK) and Basal Cell Carcinoma (BCC), as well as Dermatofibroma (DF), which is benign. A total of 330...
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2023
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| オンライン･アクセス: | http://irep.iium.edu.my/103899/1/103899_Skin%20cancer%20diagnostics%20a%20VGGEnsemble%20approach.pdf http://irep.iium.edu.my/103899/ https://link.springer.com/chapter/10.1007/978-981-19-8937-7_5 |
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my.iium.irep.1038992023-03-09T06:26:47Z http://irep.iium.edu.my/103899/ Skin cancer diagnostics: a VGGEnsemble approach Arzmi, Mohd Hafiz P.P. Abdul Majeed, Anwar Musa, Rabiu Muazu Mohd Razman, Mohd Azraai Gan, Hong-Seng Mohd Khairuddin, Ismail Ab. Nasir, Ahmad Fakhri R Medicine (General) The human skin is the largest organ of the human body, and it is highly susceptible to lesions. This study attempts to classify two distinct classes of malignant skin cancers, i.e., Actinic Keratosis (AK) and Basal Cell Carcinoma (BCC), as well as Dermatofibroma (DF), which is benign. A total of 330 dermoscopy images were split into the 70:15:15 ratio for training, testing and validation, respectively. Different VGG-Logistic Regression (LR) pipelines, i.e., VGG16-LR and VGG19-LR, were formulated. In addition, the effect of combining the features extracted from both VGG models, dubbed as VGGEnsemble, was also investigated. It was demonstrated from the study that the ensemble model yielded a better classification accuracy than its standalone versions. Therefore, it could be concluded that the performance of the pipeline is improved through this approach and subsequently could aid the diagnostics of different types of skin diseases by dermatologists. Springer 2023-01-19 Book Chapter PeerReviewed application/pdf en http://irep.iium.edu.my/103899/1/103899_Skin%20cancer%20diagnostics%20a%20VGGEnsemble%20approach.pdf Arzmi, Mohd Hafiz and P.P. Abdul Majeed, Anwar and Musa, Rabiu Muazu and Mohd Razman, Mohd Azraai and Gan, Hong-Seng and Mohd Khairuddin, Ismail and Ab. Nasir, Ahmad Fakhri (2023) Skin cancer diagnostics: a VGGEnsemble approach. In: Deep Learning in Cancer Diagnostics. SpringerBriefs in Applied Sciences and Technology (1). Springer, Singapore, pp. 27-32. ISBN 978-981-19-8936-0 https://link.springer.com/chapter/10.1007/978-981-19-8937-7_5 10.1007/978-981-19-8937-7_5 |
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Malaysia |
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| language |
English |
| topic |
R Medicine (General) |
| spellingShingle |
R Medicine (General) Arzmi, Mohd Hafiz P.P. Abdul Majeed, Anwar Musa, Rabiu Muazu Mohd Razman, Mohd Azraai Gan, Hong-Seng Mohd Khairuddin, Ismail Ab. Nasir, Ahmad Fakhri Skin cancer diagnostics: a VGGEnsemble approach |
| description |
The human skin is the largest organ of the human body, and it is highly susceptible to lesions. This study attempts to classify two distinct classes of malignant skin cancers, i.e., Actinic Keratosis (AK) and Basal Cell Carcinoma (BCC), as well as Dermatofibroma (DF), which is benign. A total of 330 dermoscopy images were split into the 70:15:15 ratio for training, testing and validation, respectively. Different VGG-Logistic Regression (LR) pipelines, i.e., VGG16-LR and VGG19-LR, were formulated. In addition, the effect of combining the features extracted from both VGG models, dubbed as VGGEnsemble, was also investigated. It was demonstrated from the study that the ensemble model yielded a better classification accuracy than its standalone versions. Therefore, it could be concluded that the performance of the pipeline is improved through this approach and subsequently could aid the diagnostics of different types of skin diseases by dermatologists. |
| format |
Book Chapter |
| author |
Arzmi, Mohd Hafiz P.P. Abdul Majeed, Anwar Musa, Rabiu Muazu Mohd Razman, Mohd Azraai Gan, Hong-Seng Mohd Khairuddin, Ismail Ab. Nasir, Ahmad Fakhri |
| author_facet |
Arzmi, Mohd Hafiz P.P. Abdul Majeed, Anwar Musa, Rabiu Muazu Mohd Razman, Mohd Azraai Gan, Hong-Seng Mohd Khairuddin, Ismail Ab. Nasir, Ahmad Fakhri |
| author_sort |
Arzmi, Mohd Hafiz |
| title |
Skin cancer diagnostics: a VGGEnsemble approach |
| title_short |
Skin cancer diagnostics: a VGGEnsemble approach |
| title_full |
Skin cancer diagnostics: a VGGEnsemble approach |
| title_fullStr |
Skin cancer diagnostics: a VGGEnsemble approach |
| title_full_unstemmed |
Skin cancer diagnostics: a VGGEnsemble approach |
| title_sort |
skin cancer diagnostics: a vggensemble approach |
| publisher |
Springer |
| publishDate |
2023 |
| url |
http://irep.iium.edu.my/103899/1/103899_Skin%20cancer%20diagnostics%20a%20VGGEnsemble%20approach.pdf http://irep.iium.edu.my/103899/ https://link.springer.com/chapter/10.1007/978-981-19-8937-7_5 |
| _version_ |
1761616130753953792 |
| score |
13.250246 |