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We generated and validated a case-mix in-hospital mortality prediction model using 50/50 split sample validation.
A hold out sample validation exercise further emphasizes the improved accuracy of the models with spatial and temporal interactions.
The study also analyzes the effect of length of training datasets and performance of split sample validation in BANNs modeling.
For the models, the electric schematics (where applicable), thermal models, accuracy, existing datasets, and sample validation plots are presented.
Integer point values were created for each predictor, and the summed risk score (range, 0 to 10) was applied to the remaining sample (validation cohort).
The sample validation strategy is outlined in Figure 1A.
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Authors additionally observe that none of the more robust studies have conducted a split-sample validation nor prospectively validated a clinical decision rule [ 31].
Using logistic regression, 2 models were generated and validated using split-sample validation: (1) One limited to preoperative characteristics (preop model) and (2) one model including both preoperative and intraoperative characteristics (combined model).
It indicated by the cross-sample validation that this survey instrument had good construct validity.
I also validate the correction approaches using an out-of-sample validation test.
It indicated by the cross-sample validation that this survey instrument also had good construct validity.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com