Breast Cancer Detection Using Explainable Artificial Intelligence
Atul Rathore, Praveen Lalwani, Pooja Lalwani · 2025
Breast cancer is the most common cause of death for women globally, accounting for one in four deaths among females. Preventing the growth of cancerous cells is made possible by early detection of breast cancer, which gives medical professionals the ability to select the best available treatments. Histopathological imaging has a substantial impact on the diagnosis and development of a disease or an illness, including breast cancer and other cancers. Recently, medical diagnoses have changed due to the application of artificial intelligence (AI) methods to histopathological analysis, including mammography, endoscopy, ultrasound, MRI, etc. The goal of this study is to give readers a comprehensive understanding of the state of video analysis and AI-assisted histopathological imaging in the context of breast cancer and others diagnosis. This article shows how data analysis and the automation of tasks like segmentation, detection, and classification can be accomplished using machine learning (ML) and deep learning algorithms. Additionally, the importance of interpretability in medical applications is discussed, as well as the topic of artificial intelligence (AI) in cancer analysis. Therefore, it will be crucial to develop clinical decision support, breast cancer diagnosis, and customized treatment procedures in order to get the best outcomes. Researchers carefully reviewed prior research on the use of AI-assisted histopathological imaging for the diagnosis and treatment of breast cancer conditions. Additionally, we support increased interdisciplinary cooperation and study in this domain.