Explainable Deep Learning in Healthcare: A Post-5G Perspective on COVID-19

This study explores the revolutionary potential of explainable deep learning models and Beyond 5G (B5G) in transforming edge healthcare applications. The study intends to improve the interpretability of diagnostic predictions by utilizing Explainable Artificial Intelligence (XAI) techniques namely SHAP and LIME, enabling professionals to make prudent decisions in telemedicine situations. The crucial requirement for explainability in automated diagnostics especially during the COVID-19 pandemic is addressed by the proposed framework. This study proves that it is feasible to provide dependable and effective healthcare services at the network edge by utilizing B5G technology, which will ultimately enhance patient outcomes and care accessibility.