Modeling Influenza with a Forest Deep Neural Network Utilizing a Virtualized Clinical Semantic Network

CoViD-19 pandemic has shown that we have deep gaps in understanding this extremely infectious virus—not only both from a clinical diagnosis and treatment perspective—but also from a forecasting point of view, so that we are better prepared for the next onset of a similar pandemic, which, at this point, seems almost inevitable. In this paper, we present a novel approach towards modeling influenza, a closely related disease to CoViD-19, marrying clinical understanding with artificial intelligence, exploiting the Forest Deep Neural Network (fDNN) with accuracy rates in the 90% range.