MelanoTech: Development of a Mobile Application Infrastructure for Melanoma Cancer Diagnosis Based on Artificial Intelligence Technologies
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.
Authors
- Halis Altun (ORCID: https://orcid.org/0000-0002-2126-8757)
- Nazlı Tokatli (ORCID: https://orcid.org/0000-0001-9840-4211)
- Gürkan Göztepeli
- Yakuphan Bılmez
- Muhammed Güler
- Furkan Karan
Institutions
- Istanbul Health and Technology University
Publication Details
- Published
- 2024-09-21
- DOI
- https://doi.org/10.1109/idap64064.2024.10710812
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00