A Study on Deep Learning Approaches for Breast Cancer Tumor Detection and Risk Prediction.

Abstract

Deep learning approaches have the potential to revolutionize breast cancer diagnosis and risk prediction. Breast cancer is the most common cancer among women worldwide, and early detection and treatment are essential for improving survival rates. This study reviews the latest deep learning techniques for breast cancer tumor detection and risk prediction, here we discusses the advantages and limitations of different deep learning models, and highlights promising areas for future research in breast cancer tumor detection using deep learning models and state-of-the-art results for breast cancer tumor detection in medical images, such as mammograms and MRIs and breast cancer risk prediction using deep learning models, here we discussed the Two common deep learning approaches for breast cancer risk prediction are logistic regression models and deep neural networks (DNNs). Deep learning approaches have the potential to revolutionize breast cancer diagnosis and risk prediction. Here we address the limitations of deep learning, it helps researchers develop more accurate, reliable, and equitable tools for breast cancer detection and risk prediction.