Using machine learning to predict nosocomial infections and medical accidents in a NICU

ConclusionThe GMERT-RI algorithm is a powerful tool. It is well suited to unearth potential correlations in the context of unbalanced panel data and discrete health outcomes, two common features of clinical data. In the particular setting of a NICU, we find that institutional features (overtime hours, occupancy rates, etc.) are just as important drivers as neonate-specific medical conditions in predicting medical accidents and health care associated infections. From an operational point of view, prediction trees can complement traditional management tools in preventing undesirable health outcomes in the NICU.
Source: Health and Technology - Category: Information Technology Source Type: research