Epidemic-guided deep learning for spatiotemporal forecasting of Tuberculosis outbreak.
Machine Learning., 2025
Tuberculosis (TB) remains a major global health challenge due to complex spatiotemporal transmission dynamics and population mobility. This work proposes an Epidemic-Guided Deep Learning (EGDL) framework that integrates a mechanistic modified Networked-SIR model with deep learning to improve forecasting accuracy and robustness. The approach combines epidemiological insights with neural networks to capture both long-term dynamics and data-driven patterns.
Overview of the Epidemic-Guided Deep Learning Architectures.