Skin Cancer Detection Using Deep Learning Approach

A deep learning approach using Convolution Neural Networks (CNNs) to recognize the occurrence of skin malignancy. The model utilizing CNN architecture is developed to precisely classify the skin lesion as benign or malignant through processing the provided dermoscopic pictures and feature extracting the vital properties like texture, form of lesion, and color of skin. It shows better outcomes when compared to present results produced by the classical machine learning approach under metrics of F1-Score, precision, recall, and accuracy. The model is effectively trained with 10,015 dermoscopic data to analyze VII types of skin lesions and assess their output in terms of different metrics.