Publication

Computers in Cardiology / Physionet Challenge 2009: Predicting Acute Hypotensive Episodes

Abstract

The goal of the Computers in Cardiology / Physionet Challenge 2009 is to predict which patients will experience acute hypotensive episode within a forecast window of one hour. In our study, statistically robust features extracted from the supplied training set were defined. A Support Vector Machine was used to classify these features. In this paper, we present our method, results and conclusion about this statistical approach.

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Related concepts (8)
Statistical assumption
Statistics, like all mathematical disciplines, does not infer valid conclusions from nothing. Inferring interesting conclusions about real statistical populations almost always requires some background assumptions. Those assumptions must be made carefully, because incorrect assumptions can generate wildly inaccurate conclusions. Here are some examples of statistical assumptions: Independence of observations from each other (this assumption is an especially common error). Independence of observational error from potential confounding effects.
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The theory of statistics provides a basis for the whole range of techniques, in both study design and data analysis, that are used within applications of statistics. The theory covers approaches to statistical-decision problems and to statistical inference, and the actions and deductions that satisfy the basic principles stated for these different approaches. Within a given approach, statistical theory gives ways of comparing statistical procedures; it can find a best possible procedure within a given context for given statistical problems, or can provide guidance on the choice between alternative procedures.
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