The aim of this study is to develop a deep learning model using Convolutional Neural Networks (CNNs) to accurately diagnose skin cancer from the ISIC-2019 dataset. This dataset contains a large collection of dermoscopic images of skin lesions, categorized into various classes including benign and malignant cases. The project involves preprocessing the images, designing and training a CNN model, and evaluating its performance in terms of accuracy, sensitivity, and specificity. By leveraging the powerful feature extraction capabilities of CNNs the model aims to provide reliable and precise diagnoses, potentially aiding dermatologists in early detection and treatment of skin cancer.
Tip
Check "CNN-Based Dermatological Cancer Diagnosis Using ISIC-2019 Dataset.pdf" for more details.
