Breast Cancer is the reason forthe most mortality rate of women worldwide.Breast cancer is the primary reason for mortality among females. There have been numerous researches done on early prediction and detection of breast cancer to start treatment and increase the chance of survival. Most of the research targets mammogram pictures. However, mammogram pictures occasionally have a threat of fake detection which can endanger the patient`s health. It is crucial to locate opportunity techniques that might be simpler to put into effect and work with extraordinary records sets, inexpensive and safer, which could produce an extra dependable prediction. This research paper proposes a combined prototype of numerous Deep Learning (DL) algorithms including Artificial Neural Network (ANN) and Convolutional Neural Networks (CNN) for efficient breast cancer prediction and detection. This research study also describes the image datasets used for breast cancer prediction, detection, and diagnosis. The proposed research prototype can be used with several data types such as text, audio, image, video, blood, urine, etc.

Deep Learning, Breast Cancer, Image Dataset, Prediction, Detection, ANN, CNN, and AI