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2498: Individual patient outcome predictions using supervised learning methods

OBJECTIVES/SPECIFIC AIMS: To learn the edit distance costs of a symbolic univariate time series representation through a stochastic finite-state transducer to predict patient outcomes in intensive care units. METHODS/STUDY POPULATION: High frequency data of patients in intensive care units were used...

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Detalles Bibliográficos
Autores principales:	Roche-Lima, Abiel, Ordoñez, Patricia, Schwarz, Nelson, Figueroa-Jiménez, Adnel, Garcia-Lebron, Leonardo A.
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Cambridge University Press 2018
Materias:	Biomedical Informatics/Health Informatics
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6799640/ http://dx.doi.org/10.1017/cts.2017.81

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