Supervised machine-learning models are feasible for predicting postinduction hypotension in anesthesiology, though performance depends on model selection and tuning.
Feasibility of machine-learning models for postinduction hypotension prediction shown; hypothesis-generating and requires prospective validation before clinical use.
The success of this technique in predicting postinduction hypotension demonstrates feasibility of machine-learning models for predictive analytics in the field of anesthesiology, with performance dependent on model selection and appropriate tuning.
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Kendale et al. (2018) studied this question.
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