Infectious Disease Forecasting via Physics-Informed Machine Learning
Joseph C Hart, Hudson Smith, Lior Rennert, Christopher S. McMahan
This paper introduces a physics-informed machine learning framework for infectious disease forecasting, showing improved accuracy in predicting case and hospitalization counts using a hybrid model of differential equations and machine learning.
bioRxiv · Jun 16, 2026 · PreprintBioinformatics