Graph convolutional network-based fusion model to predict risk of hospital acquired infections.
Hospital acquired infections (HAIs) are one of the top 10 leading causes of death within the United States. While current standard of HAI risk prediction utilizes only a narrow set of predefined clinical variables, we propose a graph convolutional neural network (GNN)-based model which incorporates a wide variety of clinical features.
Author(s): Tariq, Amara, Lancaster, Lin, Elugunti, Praneetha, Siebeneck, Eric, Noe, Katherine, Borah, Bijan, Moriarty, James, Banerjee, Imon, Patel, Bhavik N
DOI: 10.1093/jamia/ocad045