Detection and classification of skin cancer using CNN

Abstract

Recently, Artificial Intelligence (AI) has permeated all areas of scientific study due to the solutions it provides in the field of health. The most common type of cancer in the world is skin cancer. Because early recognition is crucial for improving patient outcomes, we focused our efforts on developing a skin image classification model that differentiates benign from malignant melanoma. Based on a set of data generated using the CNN model, our model is based. To train our models, we used publicly accessible sites such as Google Colab and Kaggle. In this study, we applied the CNN architecture to a variety of information containing both benign and malignant data. In this project we have achieved a high accuracy in recognizing and classifying skin cancer with a score of 91%.