Deep Learning Based Techniques for Breast Cancer Classification: A Systematic Review

Cancer represents a disease characterised by the uncontrolled growth of abnormal cells, often due to genetic mutations and environmental factors. It has the potential to infiltrate surrounding tissue and metastasize to other areas of the body. There are various types of cancer with distinct characteristics, risk factors, and treatment options. Early detection improves survival rates and reduces treatment costs. Advances in imaging technology have facilitated diagnosis, Computer-assisted systems utilize various modalities such as CT scans, MRI, ultrasound, mammography, X-rays, and histopathology to identify abnormalities.Deep learning has shown impressive results in processing large data sets within biomedicine over the past decade. The purpose of this review is to analyze and evaluate a range of pertinent research papers focusing on the application of deep learning methods for cancer detection, following the Prisma methodology. Additionally, we aim to assess current approaches to cancer diagnosis with a particular focus on techniques developed for breast cancer detection.