SkinDX: Skin Cancer Detection Using CNN

SkinDX system illustrates an adequate framework for the automation of skin disease diagnosis through the utilization of deep learning algorithms. The combination of preprocessing, feature extraction, and CNN-based classification makes the system reliable. The availability of real-time predictions in the web interface enhance accessibility to the system.

  [1]   Khan, M. A., et al. (2023). Skin Lesion Classification Using Hybrid CNN-Attention Model. Computers in Biology and Medicine.   [2]   Zhang, Y., et al. (2024). Ensemble Deep Learning Models for Multi-Class Skin Disease Detection. IEEE Transactions on Medical Imaging.   [3]   Sheller, M. J., et al. (2024). Federated Learning in Medical Imaging. Nature Scientific Reports.   [4]   Samek, W., et al. (2023). Explainable AI: Interpreting Deep Learning Models in Healthcare.   [5]   ISIC Archive (Updated 2024). Skin Imaging Dataset.   [6]   Ali, A. R., et al. (2022). Deep Learning for Skin Lesion Classification: A Review. IEEE Access.