Breast Cancer Classification using Fine Needle Aspiration Test with Graphical Neural Networks in Deep Learning
Sridevi Damodharan, G Vivekanandan, K Jeevitha, Christina Joys. S, K Designroja., Krupa. T .A · 2023
As per the statistics given by World Health Organization (WHO), in the list of reasons for women mortality, breast cancer holds the sixth place. Women in India also suffer from Breast cancer in a huge amount Breast cancer is basically the breast affected by carcinogenic cells. This can be of two types - Benign and Malignant. Benign denotes the non-spreadable cells whereas malignant cells are widely spreadable and cause several other cancers. The early the detection the easierto cure. In order to predict cancer in early stage with high accuracy, it requires the hands of technology. The main role of technology here is to predict the cancerous cells in much accurate way. Here comes the use of machine learning and deep learning. Using several neural networks, we can predict the outcomes in which each neural network performs with different accuracy levels for same data. This paper shows the detection of breast cancer type by taking the Fine Needle Aspiration (FNA) test data as input and uses the graphical neural network (GNN) to predict the type of cancer cells with higher accuracy than Convolutional Neural Network (CNN).