eXplainable AI-Enabled Deep Learning Eco System: Advancing Breast Cancer Prediction through Histological Image Analysis

Caring about health is important as loving one-self motivates a person. There are higher rates of death from breast cancer among women in the developing world due to lack of early detection and treatment. In this research, Explainable Artificial Intelligence (XAI) is applied to improve the probability of breast cancer diagnosis and increase the level of confidence in the related medical decisions. It is intended to define a model to present the AI predictions to the clinicians and the patients in an easy to understand format. The present system employs a deep learning approach that learns from a rich number of histological image cases for improved diagnosis. The patient record is updated by monitoring devices frequently, which means that treatment activities can be commenced early. The paper aims at explaining about the implementation of XAI and Case-Based Reasoning (CBR) in the development, deployment, and assessment of the system.