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Development and validation of predictive models for unplanned hospitalisation in the Basque Country: Analyzing the variability of non-deterministic algorithms

Authors: Alexander Olza; Maria Xosé Rodríguez; Eduardo Millán;

Development and validation of predictive models for unplanned hospitalisation in the Basque Country: Analyzing the variability of non-deterministic algorithms

Abstract

This release generates the results for the accompanying article. The population in most developed countries is ageing, which entails growing healthcare needs. Population-wide predictive models are crucial to address this challenge and shift the healthcare system towards preventive intervention. For this reason, we predict the probability of unplanned hospitalization in the Basque Country and identify risk groups using several techniques. When dealing with non-deterministic algorithms, comparing a single model per technique is not enough to choose the best approach. Thus, we evaluate the median performance and variability of three families of models to be able to make an informed decision. With this in mind, we achieve a double objective: Building predictive models for our specific application (unplanned hospitalisation in the Basque Country) Illustrating the need for a variability analysis in the comparison of non-deterministic algorithms

Keywords

predictive models, non-deterministic algorithms, hospitalization

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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