How machine learning is powering neuroimaging to improve brain health

NM Singh, JB Harrod, S Subramanian, M Robinson… - Neuroinformatics, 2022 - Springer
This report presents an overview of how machine learning is rapidly advancing clinical
translational imaging in ways that will aid in the early detection, prediction, and treatment of …

A narrative review illustrating the clinical utility of electroencephalogram-guided anesthesia care in children

CL Bong, GA Balanza, CEH Khoo, JSK Tan… - Anesthesia & …, 2023 - journals.lww.com
The major therapeutic end points of general anesthesia include hypnosis, amnesia, and
immobility. There is a complex relationship between general anesthesia, responsiveness …

Electroencephalogram burst-suppression during cardiopulmonary bypass in elderly patients mediates postoperative delirium

JC Pedemonte, GS Plummer, S Chamadia… - …, 2020 - pubs.asahq.org
Background Intraoperative burst-suppression is associated with postoperative delirium.
Whether this association is causal remains unclear. Therefore, the authors investigated …

Machine learning of EEG spectra classifies unconsciousness during GABAergic anesthesia

JH Abel, MA Badgeley, B Meschede-Krasa… - Plos one, 2021 - journals.plos.org
In current anesthesiology practice, anesthesiologists infer the state of unconsciousness
without directly monitoring the brain. Drug-and patient-specific electroencephalographic …

Delta oscillations phase limit neural activity during sevoflurane anesthesia

S Chamadia, JC Pedemonte, EY Hahm… - Communications …, 2019 - nature.com
Understanding anesthetic mechanisms with the goal of producing anesthetic states with
limited systemic side effects is a major objective of neuroscience research in …

Sevoflurane requirements during electroencephalogram (EEG)-guided vs standard anesthesia care in children: a randomized controlled trial

MHY Long, EHL Lim, GA Balanza, JC Allen Jr… - Journal of Clinical …, 2022 - Elsevier
Abstract Study Objectives Intra-operative electroencephalographic (EEG) monitoring
utilizing the spectrogram allows visualization of children's brain response during anesthesia …

Monitoring level of hypnosis using stationary wavelet transform and singular value decomposition entropy with feedforward neural network

MI Dutt, W Saadeh - IEEE Transactions on Neural Systems and …, 2023 - ieeexplore.ieee.org
Classifying the patient's depth of anesthesia (LoH) level into a few distinct states may lead to
inappropriate drug administration. To tackle the problem, this paper presents a robust and …

Monitoring of anesthetic depth and EEG band power using phase lag entropy during propofol anesthesia

HW Shin, HJ Kim, YK Jang, HS You, H Huh, YJ Choi… - BMC …, 2020 - Springer
Background Phase lag entropy (PLE) is a novel anesthetic depth indicator that uses four-
channel electroencephalography (EEG) to measure the temporal pattern diversity in the …

Decreased electroencephalographic alpha power during anesthesia induction is associated with EEG discontinuity in human infants

JY Chao, R Gutiérrez, AD Legatt… - Anesthesia & …, 2022 - journals.lww.com
BACKGROUND: Electroencephalogram (EEG) discontinuity can occur at high
concentrations of anesthetic drugs, reflecting suppression of electrocortical activity. This …

A pharmacokinetic and pharmacodynamic study of oral dexmedetomidine

S Chamadia, JC Pedemonte, LE Hobbs, H Deng… - …, 2020 - pubs.asahq.org
Background Dexmedetomidine is only approved for use in humans as an intravenous
medication. An oral formulation may broaden the use and benefits of dexmedetomidine to …