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BACKGROUND Nutritional support has been recognized as an essential part of intensive care unit management. However, the appropriate caloric intake for critically ill patients remains ill defined. OBJECTIVE We examined the effect of permissive underfeeding compared with that of target feeding and of intensive insulin therapy (IIT) compared with that of(More)
Many scientific and engineering applications require optimization methods to find more than one solution to multimodal optimization problems. This paper presents a new particle swarm optimization (PSO) technique to locate and refine multiple solutions to such problems. The technique, NichePSO, extends the inherent unimodal nature of the standard PSO(More)
OBJECTIVE Recent literature showed that development of hypomagnesemia is associated with higher mortality. The objective of this study is to evaluate the impact of magnesium supplementation on mortality rates of critically ill patients. METHODS All patients admitted to the Intensive Care Unit (ICU) of King Abdul-Aziz Medical City, Riyadh, Saudi Arabia(More)
BACKGROUND Clinical effects and outcomes of a single dose etomidate prior to intubation in the intensive care setting is controversial. The aim of this study is to evaluate the association of a single dose effect of etomidate prior to intubation on the mortality of septic cirrhotic patients and the impact of the subsequent use of low dose hydrocortisone. (More)
INTRODUCTION Hyperglycemia represents an independent prognostic factor in critically ill non-diabetic patients but not in those with diabetes. In this context, there is an ongoing debate on the benefit of an intensive insulin therapy, particularly in diabetic patients. We tested the hypothesis that expression of the receptor for advanced glycation(More)
Active learning algorithms allow neural networks to dynamically take part in the selection of the most informative training patterns. This paper introduces a new approach to active learning, which combines an unsupervised clustering of training data with a pattern selection approach based on sensitivity analysis. Training data is clustered into groups of(More)
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