Forecasting Cardiovascular Health Indicators with Single and Hybrid Deep Learning Models
Objective: To compare single and hybrid deep learning models for forecasting six aggregate cardiovascular health indicators at two-, five-, and ten-year horizons. Methods: Convolutional neural networks (CNN), long short-term memory networks (LSTM), gated recurrent units (GRU), and three hybrid architectures were compa...