A Deep-Learning-Based Novel Method to Classify Breast Cancer
Soham Saha, Ahona Dutta, Sabarna Choudhury · 2024
With the global health crisis of breast cancer, which is expected to affect about 2.3 million people by 2020, it is clear that there is increasing need for developing early detection tools. This study has achieved 98.25% diagnosis accuracy by using the combination of Deep Neural Network (DNN) and Machine Learning (ML) algorithms, signifying a major improvement in breast cancer detection. This study represents the recent advances in breast cancer detection research and has the potential to totally revolutionize and redefine the current techniques. The proposed approach has the potential to transform breast cancer diagnosis and enhance patient care and outcomes by utilizing data vi su a liz ation and analytical techniques.