A long short-term memory ensemble approach for improving the outcome prediction in intensive care unit

DOI10.1155/2019/8152713zbMath1428.92058OpenAlexW2988998929WikidataQ91895358 ScholiaQ91895358MaRDI QIDQ2283786

Yanyan Li

Publication date: 13 January 2020

Published in: Computational \& Mathematical Methods in Medicine (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2019/8152713

zbMATH Keywords

intensive care unitmemory ensemble approachoutcome prediction

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Medical applications (general) (92C50)

Cites Work

• Bagging predictors
• A weight-adjusted voting algorithm for ensembles of classifiers
• Advances in Neural Networks – ISNN 2005
• Random forests
• Using iterated bagging to debias regressions

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