Salvatore Giugliano

The Regularization via Gradient Attribution (RGA) framework is proposed, a module that leverages gradient-based eXplainable Artificial Intelligence (XAI) attribution maps as active supervisory signals during training that represents a methodologically grounded approach compatible with IoMT-oriented precision-medicine pipelines, while requiring dedicated deployment validation before clinical or edge-device implementation.