Automated Breast Cancer Detection Model: A Novel Customized AlexNet Model
Shubhajit Das, Debendra Muduli, Rajesh Kumar Gouda, Satya Prakash Sahu, Pratik Kumar Sahu, Santosh Kumar Sharma · 2024
Breast cancer poses a significant global health challenge, underscoring the need for effective diagnostic tools. This study introduces an automated breast cancer detection system utilizing deep learning techniques. By utilizing a dataset containing benign and malignant breast tissue images, transfer learning with a pre-trained AlexNet model is applied to extract pertinent features and train a binary classifier. The results showcase the model’s strong performance, achieving high precision, recall, and F1-score values for both benign and malignant classes, with an impressive overall accuracy of 97%. These findings demonstrate how deep learning may help diagnose breast cancer more accurately, which would be extremely helpful for early detection and treatment.