Supervised machine-learning models are feasible for predicting postinduction hypotension in anesthesiology, though performance depends on model selection and tuning.
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.
Kendale et al. (Fri,) studied this question.