Taking the advantage of EHR, data collection becomes easy and can be classified for statistical purpose immediately. For example, there are ICD-9-CM codes for diagnosis and procedure codes for chest tube insertion, we applied simple query to get the information immediately. EHR is still limited for information collection, such as vital signs, adverse events of medications and procedures, and even patients�� DAPT complaints and laboratory testing reports if patient-specific health records or history progress notes are not well constructed. At the time of data collection during period of 2004�C2005, such effective system was not available. Discussion with infection specialists for reflecting the clinical situations was done then we calculated the number of diagnosis at admission represented as Temozolomide complexity of disease, opted for general anesthesia for those who had major surgical procedures and interventions, advised for hemodialysis as the predictors of underlying healthy status. Interventional procedures or devices used, including endotracheal tube and tracheostomy, nasogastric tube, arterial line and central venous catheterization , Foley catheterization, and draining tubes implantation were recorded. The medications such as systemic glucocorticosteroids used for more than 5 days; non-steroid antiinflammatory drugs , stress ulcer prophylaxes and chemotherapeutic agents for more than 3 days were also collected. There are 16 variables including 2 demographic, 3 underlying health status-related, 7 procedural, and 4 therapeutical variables. The characters of demographic data and coding for variables with univariate analyses for both groups are shown in table 2. The major outcome is infectious or non-infectious. The set of data obtained from EHR was randomly divided into three groups: training set, selection set and test set. The training set with 927 cases, as approximately 50% of the entire cohort, was used to build LR and ANN models. The selection set of 464 cases was used for ANN modeling in avoiding overfitting and as an early stopping method ; and the test set represents 461 cases for internal validation. Multiple logistic regression analysis was first performed using the same training set of 927 cases as the ANN analysis for maximum likelihood estimation. Although the LR does not involve ����training����, we used this training set to refer to the portion of data used to derive the regression equation. A backward stepwise algorithm was used to construct the LR model and estimate the coefficient of the variables. The likelihood ratio test was used to assess the covariate-adjusted p value. Based on the result, the probability of infection was estimated using the logistic equation.