Multiclassifier Systems for Predicting Neurological Outcome of Patients with Severe Trauma and Polytrauma in Intensive Care Units.

This paper presents an ensemble based classification proposal for predicting neurological outcome of severely traumatized patients. The study comprises both the whole group of patients and a subgroup containing those patients suffering traumatic brain injury (TBI). Data was gathered from patients hospitalized in the Intensive Care Unit (ICU) of the University Hospital in Salamanca.

Success/Failure Prediction of Noninvasive Mechanical Ventilation in Intensive Care Units. Using Multiclassifiers and Feature Selection Methods.

Objectives: This paper addresses the problem of decision-making in relation to the administration of noninvasive mechanical ventilation (NIMV) in intensive care units.

Methods: Data mining methods were employed to find out the factors influencing the success/failure of NIMV and to predict its results in future patients. These artificial intelligence-based methods have not been applied in this field in spite of the good results obtained in other medical areas.

Vancomycin dosing assessment in intensive care unit patients based on a population pharmacokinetic/pharmacodynamic simulation.

WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT * Despite the frequent use of vancomycin in intensive care unit (ICU) patients, few studies aimed at characterizing vancomycin population pharmacokinetics have been performed in this critical population. * Population pharmacokinetics coupled with pharmacodynamic analysis, in order to optimize drug exposure and hence antibacterial effectiveness, has been little applied in these specific patients. WHAT THIS STUDY ADDS * Our population model characterized the pharmacokinetic profile of vancomycin in adult ICU patients, higher distribution volume values (V) being observed when the patient's serum creatinine (Cr(Se)) was greater than 1 mg dl(-1).