Computer-Aided Diagnosis for Breast Cancer Classification Using Deep Learning
Rishu, Laxman Singh, Pavan Kumar Shukla, Kanika Jindal · 2023
In today's world, breast Cancer is one of the most deadly diseases among women, although early detection dramatically improves survival rate. CNN Models are the category of DL architecture that was developed to improve accuracy in breast cancer categorization. Compared to traditional methods, CNN has demonstrated better classification efficiency and tumor detection in medical imaging. Based on deep CNN architectures This research provides a new breast cancer classification system. This research provides a new breast cancer classification system based on deep CNN architectures. To develop a technique for early and accurate breast cancer detection in order to avoid wasteful therapy (error 1) due to False Positive and late treatment (error 2) owing to False Negative is the main aim of this research methodology. The primary goal of this work is to prevent error 2, for which we employ Resnet-152.