A Deep Learning-Based Predictive Framework for Early Heart Disease Risk Assessment Using Multi-Factor Clinical Data
CardioAttentionNet is proposed, a novel hybrid deep learning framework that integrates residual convolutional neural networks, transformer encoders with multi-head self-attention, bidirectional long short-term memory networks, and cross-attention modules for comprehensive cardiovascular risk prediction.