Publication

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

Jean-Marc Vesin, Florian Jousset, Mathieu Lemay
2009
Conference Papers

Résumé

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.

Source officielle

https://infoscience.epfl.ch/entities/publication/80bbe523-9f53-46c4-9dbd-2d79fb93c715

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Jean-Marc Vesin, Florian Jousset, Mathieu Lemay
2009
Conference Papers

Résumé

Source officielle

https://infoscience.epfl.ch/entities/publication/80bbe523-9f53-46c4-9dbd-2d79fb93c715

À propos de ce résultat

Concepts associés (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.

Statistical theory

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.

Global Forecast System

vignette|Exemple de carte produite par le GFS, prévision des isohypses de géopotentiel et des isothermes de température à la pression de dans l'atmosphère, le tout valide 96 heures après le moment d’initialisation Le Global Forecast System (GFS) est un modèle de prévision numérique du temps du National Weather Service des États-Unis. Comme son nom l'indique, il fait ses calculs en utilisant les données météorologiques sur une grille qui recouvre toute la Terre. Ce modèle numérique est initialisé quatre fois par jour : 5h30, 11h30, 17h30 et 23h30.

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