Interpreting Healthcare Insights: The Power of Explainable AI and Enhanced Data Analysis

Background. This study explores the potential of Explainable AI (XAI) and Enhanced Data Analysis in improving the understanding and trustworthiness of AI models. Methods: The research focuses on integrating XAI techniques with machine learning models to provide interpretable explanations for predictions. Additionally, advanced data analysis methods are employed to gain deeper insights into the dataset and its impact on model performance. Findings: The findings highlight the benefits of XAI in enhancing model interpretability and guiding decision-making processes. Novelty and applications: Moreover, the study underscores the significance of transparent AI systems for various domains, promoting ethical use and fostering wider adoption of AI technologies.