Advanced breast cancer prediction leveraging deep convolutional neural networks
Ruchi Patira, Yogesh Kumar Gupta · 2025
Breast cancer is one of the biggest causes of mortality among women. The relative rate of survival among women with breast cancer within developed nations exceeds five years as a result of early detection and treatment. About 2.3 million cases are reported annually, according to the World Health Organization, making it the most prevalent malignancy among individuals. The ability to enhance breast cancer cell identification, decrease error rates, and expedite the human breast cancer diagnosis is a potential benefit of deep learning techniques. Breast or cervical cancer-related fatalities occur in nations with low or middle incomes at a rate of nearly 80%. One of the primary objectives of this investigation is to employ deep learning techniques to predict and evaluate the dangers associated with breast cancer. The research presents the utilization of an advanced convolutional neural network system to analyze and predict the risk of breast cancer. Our dataset employs this algorithm. Deep learning is implemented in this model to forecast the development of breast cancer by utilizing a diverse array of health characteristics.