Skin Disease Prediction Using Dynamic Testing in Machine Learning

One of the most prevalent illnesses in the modern world is skin disease. A small circular or haphazardly shaped area on the patient’s skin can be seen as a result of skin disease. When this illness develops into skin cancer, it can occasionally be very dangerous. This article discussed a few deep learning- based methods for extracting features from various skin cancer images, which can then be used with machine learning classifiers to identify the type of skin disease. A transfer learning model is created for our experiments in which a support vector machine is used for classification and the VGG- 16 layer CNN architecture is used to extract 1000 features from the input image.