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Fig 1.

Data landscape.

HIS: Hospital Information System, EMR: Electronic Medical Record, LIS: Microbiology Information System.

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Fig 1 Expand

Table 1.

Selected characteristics of the study population.

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Table 1 Expand

Table 2.

Variables used in the entry model and the HAI model.

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Table 2 Expand

Fig 2.

Illustration of the time lines of the two predictive models; the entry model and the HA-UTI model.

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Fig 2 Expand

Fig 3.

Receiver Operating Characteristic (ROC) curves for the machine learning models.

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Fig 3 Expand

Fig 4.

The cumulative lift for the entry model.

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Fig 4 Expand

Table 3.

The input (predictor) variables used in the decision tree machine-learning model for the UTI prediction at the time of admission (entry-model).

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Table 3 Expand

Table 4.

Univariate and multivariate analysis of the impactful predictive feature in the entry-model.

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Table 4 Expand