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Outcome prediction for heart failure telemonitoring via generalized linear models with functional covariates. (English) Zbl 1364.62254

Summary: An effective methodology for dealing with data extracted from clinical surveys on heart failure linked to the Public Health Database is proposed. A model for recurrent events is used for modelling the occurrence of hospital readmissions in time, thus deriving a suitable way to compute individual cumulative hazard functions. Estimated cumulative hazard trajectories are then treated as functional data, and they are used as covariates along with clinical survey data within the framework of generalized linear models with functional covariates.

MSC:

62P10 Applications of statistics to biology and medical sciences; meta analysis
62J12 Generalized linear models (logistic models)
62N05 Reliability and life testing

Software:

invGauss; R; COBS
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Full Text: DOI Link

References:

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