Artificial intelligence in breast cancer detection: Techniques and trends
Shuchi Sharma, Amandeep Kaur, Pummy Dhiman · 2025
The fastest and commonly expanding illness in the world is breast cancer. The majority of cases of breast cancer occur in women. Breast tumors can be controlled by early detection. Numerous instances are managed with early discovery, which lowers the fatality rate. Breast cancer has been the subject of a variety of studies. The most widely used research method is Machine learning. Numerous earlier studies were carried out using machine learning. Decision trees, KNNs, naïve bays, SVM, and other machine learning algorithms exhibit superior performance in their respective domains. However, a recently established method is being used to categorize breast tumors. Deep learning is the recently created approach. The shortcomings of machine learning are addressed by deep learning. Data science primarily uses deep learning techniques like recurrent neural networks, deep belief networks, convolution neural networks etc. Results from deep learning techniques are superior than those from machine learning. It extracts the images’ greatest features. In our study, the photos were classified using CNN, U-Net, and MobileNet V2. In essence, CNN is the most widely used method for image classification, and our research is based on images. All of the writers’ reviews are included in this publication, demonstrating the necessity for more research in this field.