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Towards symbolization using data-driven extraction of local trends for ICU monitoring

Abstract : We propose a methodology for the extraction of local trends from a stream of data. It has been designed to suit the needs of interpretation-oriented visualization and symbolization from ICU monitoring data. After giving implementation details for efficient computation of local trends, we propose the use of a characteristic analysis span for each variable. This characteristic span is obtained from a set of criteria that we compare and evaluate in regard of analysis of ICU monitoring data gathered within the Aiddaig project. The processing results in a rich visual representation and a framework for the local symbolization of the data stream based on its dynamics.
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https://hal.archives-ouvertes.fr/hal-01509669
Contributor : Denis Pomorski <>
Submitted on : Tuesday, April 18, 2017 - 12:38:05 PM
Last modification on : Thursday, February 21, 2019 - 10:34:09 AM

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  • HAL Id : hal-01509669, version 1

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Daniel Calvelo Aros, M.C. Chambrin, Denis Pomorski, Pierre Ravaux. Towards symbolization using data-driven extraction of local trends for ICU monitoring. Artificial Intelligence in Medicine, Elsevier, 2000, 19, pp.203-223. ⟨hal-01509669⟩

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