Measure of the prediction capability of EEG features for depth of anesthesia in pigs
Benjamin Caillet,
Gilbert Maître,
Alessandro Mirra
et al.
Abstract:Introduction: In the medical and veterinary fields, understanding the significance of physiological signals for assessing patient state, diagnosis, and treatment outcomes is paramount. There are, in the domain of machine learning (ML), very many methods capable of performing automatic feature selection. We here explore how such methods can be applied to select features from electroencephalogram (EEG) signals to allow the prediction of depth of anesthesia (DoA) in pigs receiving propofol.Methods: We evaluated n… Show more
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