Scrutiny Boosted Graph LSTM Monitoring

This research offers a thorough fuzzy-based deep learning architecture that combines a Fuzzy Pooling Convolutional Neural Network (FPCNN) for precise classification, hybrid feature extraction utilizing LeViT and SincNet. SHAP for interpretability and a Scrutiny Boosted Graph Convolutional LSTM (SBGC-LSTM) for efficient illness monitoring further improve the model.