Cloud-Based Cancer Prediction System For Enhancing Security And Authentication Using Deep Learning

Cloud-based applications are ubiquitously employed across diverse fields within the ever-evolving landscape of technology, serving as integral roots for innovation and efficiency. A meticulous evaluation of the skin cancer prediction has been done in this research, with a focus on deep neural network-based approaches. By scrutinizing a subset of 187 studies leveraging image processing techniques alongside Convolutional Neural Networks (CNNs), a profound understanding of their collective impact within various sectors emerges, allowing for a detailed exploration of their effectiveness and applications. Cancer prediction being the pivotal event of this research draw on the applications of convolutional neural network. By delving into a curated selection of studies showcasing deep neural network applications, a nuanced exploration of their efficacy within this sector is attainable, presenting an opportunity to glean insights into their practical implications and advancements. This insightful exploration acts as a beacon for future research endeavors, bringing attention to the progression of deep architectures in addressing pressing healthcare challenges and beyond. These findings underscore the paramount importance of these advancements in refining the accuracy of cancer prediction systems. In summation, this research illuminates the profound influence of deep learning methodologies, particularly convolutional neural networks, on the forefront of skin cancer prediction.