In the battle to control escalating health care costs, predictive models are increasingly employed to better allocate health care resources and to identify the “best” cases for preventive case management. In this investigation we predicted the top 0.5% most costly cases for year N+1, given a population in year N , with data for the period 1997-2001 taken from the MEDSTAT Marketscan Research Dat...

Reliability: This refers to the consistency or stability of a measure. If the concept being measured is assumed to be consistent, such as a personality trait, then the measure should yield similar results if the same person responds to it a number of times. If the concept being measured is assumed to be inconsistent, such as mood, then the measure should yield dissimilar results if a person com...

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wind energy today, has attracted widespread interest from among a variety of sources of renewable energy in the world. owing to the increasing demand for production of electrical energy for electricity networks by using wind power, it is essential that wind power plants are actively incorporated in the network’s performance using an appropriate control system. in general, these wind power plant...

a fault-tolerant control (ftc) methodology has been presented for nonlinear processes being imposed by control input constraints. the proposed methodology uses a combination of feedback linearization and model predictive control (flmpc) schemes. the resulting constraints in the transformed process will be dependent on the actual evolving states, making their incorporation in the design context ...

objective: to determine the predictive and diagnostic value of thorax trauma severity score (ttss) in a population of thoracic trauma patients admitted to a secondary level trauma center. methods : a retrospective analysis of patients admitted over a period of two years with idc-9 codes related to thoracic trauma was undertaken. the association of ttss with complications and mortality was evalu...

In recent years, there have been some interesting studies on predictive modeling in data streams. However, most such studies assume relatively balanced and stable data streams but cannot handle well skewed (e.g., few positives but lots of negatives) and skewed distributions, which are typical in many data stream applications. In this paper, we propose an ensemble and cluster based sample method...