Artificial intelligence-assisted detection model for melanoma diagnosis using deep learning techniques

Basit Öğe Kaydı
dc.contributor.authorOrhan, Hediye
dc.contributor.authorYavşan, Emrehan
dc.date.accessioned2024-10-29T17:43:41Z
dc.date.available2024-10-29T17:43:41Z
dc.date.issued2023
dc.departmentTekirdağ Namık Kemal Üniversitesi
dc.description.abstractThe progressive depletion of the ozone layer poses a significant threat to both human health and the environment. Prolonged exposure to ultraviolet radiation increases the risk of developing skin cancer, particularly melanoma. Early diagnosis and vigilant monitoring play a crucial role in the successful treatment of melanoma. Effective diagnostic strategies need to be implemented to curb the rising incidence of this disease worldwide. In this work, we propose an artificial intelligence-based detection model that employs deep learning techniques to accurately monitor nevi with characteristics that may indicate the presence of melanoma. A comprehensive dataset comprising 8598 images was utilized for the model development. The dataset underwent training, validation, and testing processes, employing the algorithms such as AlexNet, MobileNet, ResNet, VGG16, and VGG19, as documented in current literature. Among these algorithms, the MobileNet model demonstrated superior performance, achieving an accuracy of 84.94% after completing the training and testing phases. Future plans involve integrating this model with a desktop program compatible with various operating systems, thereby establishing a practical detection system. The proposed model has the potential to aid qualified healthcare professionals in the diagnosis of melanoma. Furthermore, we envision the development of a mobile application to facilitate melanoma detection in home environments, providing added convenience and accessibility. © 2023 by the authors.
dc.identifier.doi10.53391/mmnsa.1311943
dc.identifier.endpage169
dc.identifier.issn2791-8564
dc.identifier.issue2en_US
dc.identifier.scopus2-s2.0-85172890758
dc.identifier.scopusqualityN/A
dc.identifier.startpage159
dc.identifier.trdizinid1186453
dc.identifier.urihttps://doi.org/10.53391/mmnsa.1311943
dc.identifier.urihttps://search.trdizin.gov.tr/tr/yayin/detay/1186453
dc.identifier.urihttps://hdl.handle.net/20.500.11776/12565
dc.identifier.volume3
dc.indekslendigikaynakScopus
dc.indekslendigikaynakTR-Dizin
dc.language.isoen
dc.publisherMehmet Yavuz
dc.relation.ispartofMathematical Modelling and Numerical Simulation with Applications
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectArtificial intelligence
dc.subjectdeep learning
dc.subjectmachine learning
dc.subjectmelanoma detection
dc.subjectskin cancer
dc.titleArtificial intelligence-assisted detection model for melanoma diagnosis using deep learning techniques
dc.title.alternativeArtificial intelligence-assisted detection model for melanoma diagnosis using deep learning techniques
dc.typeArticle

Dosyalar

Koleksiyon

Scopus İndeksli Yayınlar Koleksiyonu
TR-Dizin İndeksli Yayınlar Koleksiyonu