Edge AI based Facial skin cancer detection system

Malignant melanoma is one!of the most aggressive and deadly forms of skin cancer, making the prompt and accurate diagnosis essential for improving patient outcomes. Unfortunately, the traditional method of relying on expert visual assessments is often subjective and limited by the availability of specialized clinicians. This research introduces an innovative computer-aided diagnostic (CADx) framework designed to revolutionize the identification of melanoma through the use of dermoscopic images and advanced deep learning techniques. Our system harnesses the power of a deep Convolutional-Neural-Network (CNN), initially trained!on!the comprehensive ImageNet database and then fine-tuned with data from the publicly available ISIC (International Skin Imaging Collaboration) dataset. This process enables the model to adeptly recognize the intricate morphological features that differentiate!benign from!malignant skin lesions. The results speak for themselves: our proposed framework achieves remarkable accuracy, sensitivity, and specificity, positioning it as a trustworthy and objective resource for dermatologists. In the critical fight against early-stage melanoma, this tool has the potential!to enhance diagnosis and ultimately save lives.