Deep Learning-Enabled Breast Cancer Detection from Histopathological Images in IoT Environments

Breast cancer is a common and serious disease in women, caused by genetic mutations in the breast cells that lead to uncontrolled cell growth and tumor formation. If not detected early, it can spread to other parts of the body. Early and accurate screening is crucial for effective treatment and lowering mortality rates. This study explores multiple techniques for breast cancer detection within the Internet of Things (IoT) framework, focusing on the application of Deep Learning (DL) and Machine Learning (ML) methods. This survey reviews 25 research papers published between 2017 and 2024 that focus on breast tumor detection in IoT environments using histopathological images. Moreover, this review highlights the strengths and weaknesses of IoT-based breast cancer detection, as presented in the 25 examined studies. The paper concludes that Deep Learning (DL) techniques are commonly utilized for detecting breast tumors in IoT environments using histopathological images.