Skin Cancer Detection Using Deep Learning and Artificial Intelligence

Detalhes bibliográficos
Autor(a) principal: Abdelaziz, Ahmed
Data de Publicação: 2022
Outros Autores: Mahmoud, Alia N.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/149799
Resumo: Abdelaziz, A., & Mahmoud, A. N. (2022). Skin Cancer Detection Using Deep Learning and Artificial Intelligence: Incorporated model of deep features fusion. Fusion: Practice and Applications, 8(2), 8-15. https://doi.org/10.54216/FPA.080201 © 2022, American Scientific Publishing Group (ASPG). All rights reserved.
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spelling Skin Cancer Detection Using Deep Learning and Artificial IntelligenceIncorporated model of deep features fusionDeep LearningImage ClassificationNeural NetworkSkin CancerComputer Science (miscellaneous)Computer Networks and CommunicationsComputer Science ApplicationsInformation SystemsSDG 3 - Good Health and Well-beingAbdelaziz, A., & Mahmoud, A. N. (2022). Skin Cancer Detection Using Deep Learning and Artificial Intelligence: Incorporated model of deep features fusion. Fusion: Practice and Applications, 8(2), 8-15. https://doi.org/10.54216/FPA.080201 © 2022, American Scientific Publishing Group (ASPG). All rights reserved.Among the most frequent forms of cancer, skin cancer accounts for hundreds of thousands of fatalities annually throughout the globe. It shows up as excessive cell proliferation on the skin. The likelihood of a successful recovery is greatly enhanced by an early diagnosis. More than that, it might reduce the need for or the frequency of chemical, radiological, or surgical treatments. As a result, savings on healthcare expenses will be possible. Dermoscopy, which examines the size, form, and color features of skin lesions, is the first step in the process of detecting skin cancer and is followed by sample and lab testing to confirm any suspicious lesions. Deep learning AI has allowed for significant progress in image-based diagnostics in recent years. Deep neural networks known as convolutional neural networks (CNNs or ConvNets) are essentially an extended form of multi-layer perceptrons. In visual imaging challenges, CNNs have shown the best accuracy. The purpose of this research is to create a CNN model for the early identification of skin cancer. The backend of the CNN classification model will be built using Keras and Tensorflow in Python. Different network topologies, such as Convolutional layers, Dropout layers, Pooling layers, and Dense layers, are explored and tried out throughout the model's development and validation phases. Transfer Learning methods will also be included in the model to facilitate early convergence. The dataset gathered from the ISIC challenge archives will be used to both tests and train the model.NOVA Information Management School (NOVA IMS)RUNAbdelaziz, AhmedMahmoud, Alia N.2023-02-27T22:23:44Z20222022-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article8application/pdfhttp://hdl.handle.net/10362/149799eng2770-0070PURE: 54222940https://doi.org/10.54216/FPA.080201info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:31:39Zoai:run.unl.pt:10362/149799Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:53:52.020571Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Skin Cancer Detection Using Deep Learning and Artificial Intelligence
Incorporated model of deep features fusion
title Skin Cancer Detection Using Deep Learning and Artificial Intelligence
spellingShingle Skin Cancer Detection Using Deep Learning and Artificial Intelligence
Abdelaziz, Ahmed
Deep Learning
Image Classification
Neural Network
Skin Cancer
Computer Science (miscellaneous)
Computer Networks and Communications
Computer Science Applications
Information Systems
SDG 3 - Good Health and Well-being
title_short Skin Cancer Detection Using Deep Learning and Artificial Intelligence
title_full Skin Cancer Detection Using Deep Learning and Artificial Intelligence
title_fullStr Skin Cancer Detection Using Deep Learning and Artificial Intelligence
title_full_unstemmed Skin Cancer Detection Using Deep Learning and Artificial Intelligence
title_sort Skin Cancer Detection Using Deep Learning and Artificial Intelligence
author Abdelaziz, Ahmed
author_facet Abdelaziz, Ahmed
Mahmoud, Alia N.
author_role author
author2 Mahmoud, Alia N.
author2_role author
dc.contributor.none.fl_str_mv NOVA Information Management School (NOVA IMS)
RUN
dc.contributor.author.fl_str_mv Abdelaziz, Ahmed
Mahmoud, Alia N.
dc.subject.por.fl_str_mv Deep Learning
Image Classification
Neural Network
Skin Cancer
Computer Science (miscellaneous)
Computer Networks and Communications
Computer Science Applications
Information Systems
SDG 3 - Good Health and Well-being
topic Deep Learning
Image Classification
Neural Network
Skin Cancer
Computer Science (miscellaneous)
Computer Networks and Communications
Computer Science Applications
Information Systems
SDG 3 - Good Health and Well-being
description Abdelaziz, A., & Mahmoud, A. N. (2022). Skin Cancer Detection Using Deep Learning and Artificial Intelligence: Incorporated model of deep features fusion. Fusion: Practice and Applications, 8(2), 8-15. https://doi.org/10.54216/FPA.080201 © 2022, American Scientific Publishing Group (ASPG). All rights reserved.
publishDate 2022
dc.date.none.fl_str_mv 2022
2022-01-01T00:00:00Z
2023-02-27T22:23:44Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/149799
url http://hdl.handle.net/10362/149799
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2770-0070
PURE: 54222940
https://doi.org/10.54216/FPA.080201
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 8
application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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