Deep Learning-based and Machine Learning-based Application in Skin Cancer Image Classification

Skin cancer arises from the skin and is capable of invading other parts of the body. The earlier detection of malignant skin lesions effectively helps cure skin disease and prevents fatal skin cancer. As part of AI, machine learning and deep learning can learn the characteristics of input datasets and perform classifications with high accuracy. In this paper, the CNN, KNN, and SVM models are implemented and tested based on the datasets collected from ISIC. The idea of the implementation is to classify the images of skin lesions into benign and malignant. The information of GANs based model is gathered. The results display the accuracy of using these models to classify different types of lesions. And the discussion of the results focuses on the efficiency to implement the machine learning and deep learning models and the accuracy of using them. The goal of the study is to figure out which method is more useful in skin cancer identification. And some of the possible practices are also discussed as future expectations.