MelanoTech: Development of a mobile application infrastructure for melanoma cancer diagnosis based on artificial intelligence technologies
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Tarih
2024
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
IEEE
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
This 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.
Açıklama
Anahtar Kelimeler
Artificial Intelligence applicaitons in Healthcare Systems, Melanoma Detection, Mobile Health Applications, Deep Learning Techniques, Dermoscopic Imaging
Kaynak
2024 8th International Artificial Intelligence and Data Processing Symposium (IDAP)
WoS Q Değeri
Scopus Q Değeri
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Sayı
Künye
Tokatlı, 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
