Classification of Early Skin Cancer Prediction using Nesterov- Accelerated Adaptive Moment Estimation (NADAM) Optimizer Algorithm

To meet the growing need for effective skin cancer identification, especially in healthcare settings, this study introduces an advanced method for skin cancer classification using the Nesterov- accelerated Adaptive Moment estimation (NADAM) optimizer algorithm. The aim is to improve accuracy and reliability in identifying skin conditions by leveraging the capabilities of NADAM for efficient detection and classification through images. The proposed system is designed to be robust and scalable, tailored specifically for healthcare applications, ensuring precise identification of various skin issues crucial for accurate diagnosis and treatment optimization. In summary, this proposed system not only contributes to enhancing the accuracy of skin cancer identification and treatment but also aligns with the evolving landscape of advanced healthcare technologies. It represents a promising step toward a future where skin cancers are diagnosed and treated with precision, supported by advanced algorithms and optimization techniques.