Control of Nosocomial Infections by Data Mining

These last 15 years have been rich in publishing high quality scientific studies evaluating the effectiveness of measures to prevent nosocomial infections, particularly in intensive care unit (ICU), comparison of the results of these studies and practices in intensive care units can now to better define a program for preventing nosocomial infections to develop in these services. Focused on managing the risk of infection and prevention of nosocomial infections, our study, using tools that use data mining methods, together proposals for how well resuscitation. Among the techniques we use in data mining classification, neural networks and decision trees that also use the description used for prevention or for the unsupervised classification and clustering, we estimate we have for the rules Association. These techniques are used with several algorithms that give different results and which are distinguished from each other.