Residual GRU+MHSA: A Lightweight Hybrid Recurrent Attention Model for Cardiovascular Disease Detection

This article presents a research paper on a novel AI model for cardiovascular disease detection. The model, named Residual GRU+MHSA, combines recurrent neural networks (GRU) with multi-head self-attention (MHSA) to create a lightweight hybrid architecture. The focus is on efficiency and performance in the context of medical diagnosis. The source being ArXiv suggests this is a preliminary publication, likely undergoing peer review.

• •The research focuses on a lightweight AI model for cardiovascular disease detection.
• •The model combines GRU and MHSA for a hybrid architecture.
• •The paper is likely a preliminary publication on ArXiv.