MelanoTech: Development of a mobile application infrastructure for melanoma cancer diagnosis based on artificial intelligence technologies

Basit Öğe Kaydı
dc.authorid0000-0002-2126-8757
dc.contributor.authorTokatlı, Nazlı
dc.contributor.authorBilmez, Yakuphan
dc.contributor.authorGöztepeli, Gürkan
dc.contributor.authorGüler, Muhammed
dc.contributor.authorKaran, Furkan
dc.contributor.authorAltun, Halis
dc.date.accessioned2024-10-23T08:32:18Z
dc.date.available2024-10-23T08:32:18Z
dc.date.issued2024
dc.departmentFakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Bilgisayar Mühendisliği Bölümü
dc.departmentFakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Yazılım Mühendisliği Bölümü
dc.description.abstractThis preliminary work introduces MelanoTech, a mHealth application designed and implemented to offer a user-friendly and intuitive interface for the early diagnosis of melanoma, a kind of skin cancer with significant fatality rates [1]. The application demonstrates promising performance in segmentation and classification tasks by utilizing deep learning models with Generative Adversarial Networks (GANs) for data augmentation. MelanoTech achieves a comprehensive accuracy rate of 92%, with a segmentation model accuracy rate of 93% and a lesion detection accuracy rate of 90%. Finally, incorporating data augmentation approaches based on GANs resulted in a 5% enhancement in the model’s performance. These findings highlight the capacity of MelanoTech as a dependable tool for improving the early diagnosis of melanoma and decreasing the workload of physicians in Turkish public hospitals.
dc.identifier.citationTokatlı, N., Bilmez, Y., Göztepeli, G., Güler, M., Karan, F. & Altun, H. (2024). MelanoTech: Development of a mobile application infrastructure for melanoma cancer diagnosis based on artificial intelligence technologies. 2024 8th International Artificial Intelligence and Data Processing Symposium (IDAP), pp. 1-6. Malatya, Turkiye. https://doi.org/10.1109/IDAP64064.2024.10710812
dc.identifier.doi10.1109/IDAP64064.2024.10710812
dc.identifier.endpage6
dc.identifier.scopus2-s2.0-85207880802
dc.identifier.startpage1
dc.identifier.urihttps://doi.org/10.1109/IDAP64064.2024.10710812
dc.identifier.urihttps://hdl.handle.net/20.500.13055/834
dc.institutionauthorTokatlı, Nazlı
dc.institutionauthorBilmez, Yakuphan
dc.institutionauthorGöztepeli, Gürkan
dc.institutionauthorGüler, Muhammed
dc.institutionauthorKaran, Furkan
dc.institutionauthorAltun, Halis
dc.institutionauthorid0000-0002-2126-8757
dc.language.isoen
dc.publisherIEEE
dc.relation.ispartof2024 8th International Artificial Intelligence and Data Processing Symposium (IDAP)
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectArtificial Intelligence applicaitons in Healthcare Systems
dc.subjectMelanoma Detection
dc.subjectMobile Health Applications
dc.subjectDeep Learning Techniques
dc.subjectDermoscopic Imaging
dc.titleMelanoTech: Development of a mobile application infrastructure for melanoma cancer diagnosis based on artificial intelligence technologies
dc.typeConference Object
dspace.entity.typePublication

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