In the clinical decision-making context, Artificial Intelligence (AI) models can reveal patterns and insights that are beyond human predictive capacity due to the extreme volume and complexity of healthcare data. In that context, the present research work introduces and details the design and implementation of the Explainable Dashboard Hub (EDH), which contains a collection of many different explainable dashboards and approaches for AI models, as well as comparisons of these different models for different cases. It is an interactive framework with user-friendly interfaces that healthcare professionals can gain knowledge through an organized and comprehensive way. The EDH strengthens the ethical and clinical foundation of digital health innovation, as it ensures that AI-driven healthcare becomes explainable, accessible, and personalized.