Quantitative electroencephalogram and machine learning to predict expired sevoflurane concentration in infants

Processed electroencephalography (EEG) indices used to guide anesthetic dosing in adults are not validated in young infants. Raw EEG can be processed mathematically, yielding quantitative EEG parameters (qEEG). We hypothesized that machine learning combined with qEEG can accurately classify expired sevoflurane concentrations in young infants. Knowledge from this may contribute to development of future infant-specific EEG algorithms.

Citation:
Kumar R, Skowno J, von Ungern-Sternberg BS, Davidson A, …….. Sommerfield D, Sheppard S, Menezes M. Quantitative electroencephalogram and machine learning to predict expired sevoflurane concentration in infants. J Clin Monit Comput. 2025.

Keywords:
Infant electroencephalogram EEG; Machine learning; Pediatric EEG anesthesia; Quantitative EEG anesthesia; SHAP EEG analysis.

Abstract:
Processed electroencephalography (EEG) indices used to guide anesthetic dosing in adults are not validated in young infants. Raw EEG can be processed mathematically, yielding quantitative EEG parameters (qEEG). We hypothesized that machine learning combined with qEEG can accurately classify expired sevoflurane concentrations in young infants. Knowledge from this may contribute to development of future infant-specific EEG algorithms.