Explainable Artificial Intelligence in Healthcare -A Review
S. Ishwarya, Anitha S. Pillai · 2024
This study focuses on the application of Explainable Artificial Intelligence (XAI) in Stroke, heart attack and cancer prediction, highlighting the importance of XAI. This technology helps users to clearly understand the reason behind detection, prediction and classification. XAI further enhances the capabilities of these models ensuring that their predictions are accurate but also transparent, interpretable, and actionable. This paper explores recent research and developments in XAI Applications for three healthcare domains. It also examines the algorithm, datasets, and accuracy achieved, shedding light on how XAI has improved the accuracy and trustworthiness of predictive models. This study thoroughly analyses Explainable AI’s effect on healthcare, delivering insightful information about how XAI is changing the field of predictive medicine and enhancing patient outcomes and healthcare decision-making.