Computer-Assisted Diagnostic Tool Package for Real-Time Analysis of Skin Disorder

Skin cancer constitutes one of the most common types of cancer, and according to the World Health Organization, one in five people will develop skin cancer before the age of 70. More than 3.5 million new cases occur annually in the USA, and that number continues to rise. The crucial point for treating skin cancer is early and accurate detection. For this purpose, a standalone diagnostic software tool package with a computer-aided effective system and a real-time classifier using machine learning and deep learning algorithms to classify the skin disorders based on their physiological features through A(asymmetry), B(boundary), C(color), D(diameter) which is deployed in this tool. A combined model of learning algorithms is defined for the detection of different skin disorders to improve efficiency. Thus, a software tool package with systemic learning algorithms of 98% efficiency is developed for the detection of different skin disorders.