Consciousness and complexity: a consilience of evidence

S Sarasso, AG Casali, S Casarotto… - Neuroscience of …, 2021 - academic.oup.com
Over the last years, a surge of empirical studies converged on complexity-related measures
as reliable markers of consciousness across many different conditions, such as sleep …

Length of stay prediction for ICU patients using individualized single classification algorithm

X Ma, Y Si, Z Wang, Y Wang - Computer methods and programs in …, 2020 - Elsevier
Abstract Background and Objective: In intensive care units (ICUs), length of stay (LOS)
prediction is critical to help doctors and nurses select appropriate treatment options and …

Design and implementation of a machine learning based EEG processor for accurate estimation of depth of anesthesia

W Saadeh, FH Khan, MAB Altaf - IEEE transactions on …, 2019 - ieeexplore.ieee.org
Accurate monitoring of the depth of anesthesia (DoA) is essential for intraoperative and
postoperative patient's health. Commercially available electroencephalograph (EEG)-based …

Time‐Frequency Analysis of EEG Signals and GLCM Features for Depth of Anesthesia Monitoring

SM Mousavi, A Asgharzadeh-Bonab… - Computational …, 2021 - Wiley Online Library
One of the important tasks in the operating room is monitoring the depth of anesthesia (DoA)
during surgery, and noninvasive techniques are very popular. Hence, we propose a new …

Harnessing machine learning for EEG signal analysis: Innovations in depth of anaesthesia assessment

T Schmierer, T Li, Y Li - Artificial Intelligence in Medicine, 2024 - Elsevier
Anaesthesia, crucial to surgical practice, is undergoing renewed scrutiny due to the
integration of artificial intelligence in its medical use. The precise control over the temporary …

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 …

Constructing a consciousness meter based on the combination of non-linear measurements and genetic algorithm-based support vector machine

Z Liang, S Shao, Z Lv, D Li, JW Sleigh… - … on Neural Systems …, 2020 - ieeexplore.ieee.org
Objective: Constructing a framework to evaluate consciousness is an important issue in
neuroscience research and clinical practice. However, there is still no systematic framework …

Automated tracking of level of consciousness and delirium in critical illness using deep learning

H Sun, E Kimchi, O Akeju, SB Nagaraj… - NPJ digital …, 2019 - nature.com
Over-and under-sedation are common in the ICU, and contribute to poor ICU outcomes
including delirium. Behavioral assessments, such as Richmond Agitation-Sedation Scale …

A multilayer perceptron (MLP) regressor network for monitoring the depth of anesthesia

MI Dutt, W Saadeh - 2022 20th IEEE Interregional NEWCAS …, 2022 - ieeexplore.ieee.org
Monitoring the depth of anesthesia (DoA) during surgical procedures is very critical for
patients' health. Any inaccurate dosage of the anesthetic agents can result in postoperative …

An EEG-based hypnotic state monitor for patients during general anesthesia

FH Khan, W Saadeh - IEEE Transactions on Very Large Scale …, 2021 - ieeexplore.ieee.org
Most surgical procedures are not possible without general anesthesia which necessitates
continuous and accurate monitoring of the patients' level of hypnosis (LoH). Currently, the …