Proposed Cnn Model For Breast Cancer Detection

lead to a longer lifespan. Breast cancer is a leading cause of death among women worldwide. In this study, we designed a proposed convolutional neural network (CNN) model that consisting of 39 layers. The model begins with feature extraction from input mammogram images using a series of convolutional layers, batch normalization, ReLU activation functions, and max-pooling layers. This is followed by six fully connected layers for classification. Overall, the proposed model includes a three-layer feature extractor and a two-layer decision-making module designed specifically for breast cancer detection. The model achieved impressive performance metrics, with an accuracy of 98%, precision of 95%, recall of 96%, and an F-score of 96.4% if number of epoch equal to 5 and 100% if epoch equal to 10.