2 resultados para intra prediction

em Deakin Research Online - Australia


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The vision of next generation networks (4G & beyond) is to make possible seamless mobility across heterogeneous networks and to support real-time multimedia services. This would require intra/inter-domain handovers and service reconfiguration procedures to be completed with minimum latency. Mobility Prediction has been identified as a key abettor to this goal. The increasing ease of coupling between the mobile user and the network requires that a mobility prediction scheme that is to be deployed in next generation networks be capable of high levels of prediction accuracy despite randomness in user movement. In this work we have presented a survey on mobility prediction schemes that have been proposed for wireless networks. The results of our simulation study focused on the robustness of different schemes to randomness in user movement are also presented.

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Aim: The aim of this paper was to review the implications that variable definitions have for the prediction of post-operative pulmonary complications after cardiac surgery.

Method: A review of the literature from 1980 to 2002. Selected studies demonstrated an original attempt to examine multivariate associations between pre, intra or post-operative antecedents and pulmonary outcomes in patients undergoing coronary artery bypass grafting (CABG). Reports that described the validation of established clinical prediction rules, testing interventions or research conducted in non-human cohorts were excluded from this review.

Results: Consistently, variable factor and outcome definitions are combined for the development of multivariate prediction models that subsequently have limited clinical value. Despite being prevalent there are very few attempts to examine post-operative pulmonary complications (PPC) as endpoints in isolation. The trajectory of pulmonary dysfunction that precedes complications in the post-operative context is not clear. As such there is little knowledge of post-operative antecedents to PPC that are invariably excluded from model development.

Conclusion: Multivariate clinical prediction rules that incorporate antecedent patient and process factors from the continuum of cardiovascular care for specific pulmonary outcomes are recommended. Models such as these would be useful for practice, policy and quality improvement.