A Complete Analysis of Explainable AI and Its Methods for Healthcare Prediction
A. Vinora, E. Lloyds, M. Soundarya · Auerbach Publications eBooks · 2025
Healthcare is the prime concern for the welfare of the society. High-end technology is adapted in the healthcare industry, like artificial intelligence, helps to manage and control hospitals, clinics, and emergency care facilities. Advancement in technologies has helped to provide dynamic solutions in healthcare that has benefitted an enormous population. Highly intensive diseases can be diagnosed and treated in advance to reduce the severity of the impact. Individual care can be deployed based on state-of-the-art technology used to analyze patient-centric issues providing personalized care. Artificial intelligence (AI) in healthcare services has led to the development of models built to study and analyze the patterns of various diseases that help to derive a pattern that can be decrypted to treat the disease effectively. AI encapsulated along with domains such as medical imaging has proved to be effective in obtaining results and continues to be a support system in modern health-care. The greatest challenge of AI models is the ability to make decisions in healthcare that can potentially lead to trust issues and a lack of confidentiality, security, and liability. AI has given results without further justifications on its decisions that had led to ambiguity in the accuracy of decision-making to overcome such shortfall we are have introduced explainable AI in healthcare, that gives an insight on the justification of the decisions made. It further explains the various methods adopted by explainable AI in healthcare to achieve the same.