Melanoma Disease Detection Using Convolutional Neural Networks

There are different forms of cancers out of which skin cancer is the most common one, Usually, Every year the people infected by Skin Cancer will be more than the number of people infected by all other types of cancer combined. Mortality rates of skin cancer in the world have risen. According to the World Health Organization, the early finding of transformations of the skin significantly improve the chances of good medication and treatment so that the patient can be saved. The Computer system integrated with the software developed from deep learning, namely convolutional neural networks (CNN), is good at detecting skin cancer than experienced dermatologists, so now We had extended this Deep Learning Architecture to develop a model that categorizes the given infected skin image of patient as Malignant (Melanoma or Harmful) or Benign (Harmless) By using various libraries in Python. This model is trained and tested by using dataset taken from International Skin Imaging Collaboration(ISIC). The main aim of this model is to detect skin cancer for patients in earlier stages and treat them effectively so that we can reduce the mortality rate.