Background: Hospital-acquired infections (HAI) are associated with increased attributable morbidity, mortality, prolonged hospitalization, and economic costs. A simple, reliable prediction model for HAI has great clinical relevance. The objective of this study is to develop a scoring system to predict HAI that was derived from Logistic Regression (LR) and validated by Artificial Neural Networks (ANN) simultaneously.
In a study conducted in Taiwan, REF linear regression (LR) and artificial neural networks (ANNs) were used to predict HAI.
Predicting Hospital-Acquired Infections by Scoring System with Simple Parameters
PLoS ONE
PLoS ONE
Medicine