Publication

Abstract : Explainable Artificial Intelligence or (XAI) be-coming more popular in machine learning field because it allows the users to interpret most clear result and also provide public trust and facilitate their development and deployment of AI systems.Encouraging AI models to be more transparent and understandable is the aim of the burgeoning field of explainable AI.Here, we cover a varied scope of XAI for a healthcare-based retrieval system. When a user queries a healthcare-related document, XAI may explain why it was retrieved. Patients who make use of the XAI tools will be better able to comprehend the advice and be more inclined to believe it. The article also covers several additional uses for XAI models, including manufacturing and banking. Within the healthcare industry, medical diagnostic systems’ predictions may also be defined by using explainable AI models. This is crucial for applications in the healthcare industry since it’s required to comprehend the reasons behind predictions made by AI.