Interpatient Heartbeat Classification Using Modified Residual Attention Network With Two-Phase Training and Assistant Decision

Exploring the Applicability of Transfer Learning and Feature Engineering in Epilepsy Prediction Using Hybrid Transformer Model

“…Especially, convolutional neural networks (CNNs) have gained maximum attention in epilepsy prediction [14], [15]. However, many DL models including CNNs ignore the key factor of attention, which will result in each feature of the input being an equal competitor, and the neural network must additionally learn the weights corresponding to the features to achieve the purpose of distinguishing the importance of features, which will result in a complex and heavy model [16], [17].…”