Outcome Prediction for Heart Failure Telemonitoring Via Generalized Linear Models with Functional Covariates |
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| Authors: | STEFANO BARALDO FRANCESCA IEVA ANNA MARIA PAGANONI VALERIA VITELLI |
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| Affiliation: | 1. MOX – Modeling and Scientific Computing, Department of Mathematics ‘F. Brioschi’, Politecnico di Milano;2. Chair on Systems Science and the Energetic Challenge, European Foundation for New Energy –électricité de France, école Centrale Paris and Supélec (école Supérieure d’électricité) |
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| Abstract: | 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. |
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| Keywords: | functional data analysis generalized linear models Public Health Database recurrent events processes |
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