Detection and Predictive Analysis of COVID-19 Based on Optimized Situational Aware Multi Graph Convolutional Recurrent Network

Key Points

• COVID-19 detection shows improved accuracy through an optimized multi graph convolutional recurrent network.
• The predictive model achieved a 15% increase in accuracy compared to traditional methods across diverse datasets.
• Analysis using advanced algorithms showcased the effectiveness of situational awareness in predicting disease spread.
• These findings support the potential of AI-driven methods in enhancing public health responses during outbreaks.