Novel Deep Learning Neural Networks for Breast Cancer Malignancy Estimation
DOI:
https://doi.org/10.37934/araset.47.1.140151Keywords:
Artificial Neural Network (ANN), Deep Neural Network (DNN) , Adaptive Moment Estimation (ADAM), Lasso Regression (L1) , Categorical Cross-Entropy (CCE)Abstract
Medicine has become one of the huge fields which has its own growth each and every day. Few diseases are still a threat to medical field. Because of its destructive nature, cancer is a disease that causes fear in many people throughout the world. However, most cancers are curable if detected early and treated with the right medical care and computer-assisted diagnosis. These days, diagnosis is more popular because it works well as a primary screening test for many diseases, particularly cancer. Deep learning is a method of artificial intelligence where the computer is given intelligence that attempts to emulate the way a human brain thinks. This research focuses on creating a deep neural network that can accurately predict the malignancy of breast cancer up to 98%, allowing medical personnel to diagnose patients more quickly and administer therapy more effectively.