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Using Machine Learning to Predict Nosocomial Infections and Medical Accidents in a NICU

23 Apr 2020

The final sample thus includes 5,466 neonates and represents over 101,621 infant/days over the sample period.3 Table 1 provides the means of the main variables used in the models. [...] The table shows that proportionately more MA occurred in the months that followed the reform relative to either the popula- tion of neonates or to those with a HCAI. [...] The analysis of MA fur- ther includes daily regular and overtime hours in the NICU as well as a dummy variable equal to one if the infant incurred a HCAI prior to the MA. [...] The first number inside each node corresponds to the predicted probability of reaching the latter.5 The number of observations (n) in appears just below the node. [...] The main idea is to fit a tree after removing the random effects part of the model, update the estimates (or predictions) of the random effect and cycle until convergence.
health economics machine learning science and technology mathematics medicine nursing regression analysis health care paediatrics health sciences cross validation errors and residuals cross-validation (statistics) hospital and clinic dependent and independent variables error covariates generalized linear model nicu decision tree learning cross-validation cart regression tree neonatal intensive care unit decision tree gini impurity

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ISSN
22920838
Pages
18
Published in
Montreal, QC, CA

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