Published Paper Details:

Breast cancer is the most common and rapidly developing disease in the world. Breast cancer is most commonly detected in women. Breast cancer can be controlled if it is detected early. Many instances are addressed by early detection, which reduces the death rate. Many studies on breast cancer have been conducted. Machine learning is the most commonly utilised technique in research. There have been numerous previous studies conducted using machine learning. Machine learning techniques such as decision trees, KNN, SVM, nave bays, and others provide superior performance in their respective fields. However, a newly established approach is being utilised to classify breast cancer. Deep learning is a newly developed method. Deep learning is used to compensate for the shortcomings of machine learning. Convolution neural network, recurrent neural network, deep belief network, and other deep learning techniques are commonly utilised in data science. When compared to machine learning, deep learning algorithms produce greater results. It extracts the images' greatest features. CNN is employed to classify photos in our study. Our research is primarily image-based, and CNN is the most widely used technique for image classification. The current document includes reviews of all writers