Time-frequency transform plus per-slice gradient boosting detects EEG bursts in preterm infants with AUC 0.98, matching multi-feature baselines.
Line length as a robust method to detect high- activity events: automated burst detection in premature EEG record- ings
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
eess.SP 1years
2019 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Machine learning without a feature set for detecting bursts in the EEG of preterm infants
Time-frequency transform plus per-slice gradient boosting detects EEG bursts in preterm infants with AUC 0.98, matching multi-feature baselines.