Deep-Learning-Based Automated Anomaly Detection of EEGs in Intensive Care Units
JCH Wu, NC Liao, TH Yang, CC Hsieh, JA Huang… - Bioengineering, 2024 - mdpi.com
An intensive care unit (ICU) is a special ward in the hospital for patients who require
intensive care. It is equipped with many instruments monitoring patients' vital signs and …
intensive care. It is equipped with many instruments monitoring patients' vital signs and …
Graph convolutional network for generalized epileptiform abnormality detection on EEG
D Nhu, M Janmohamed, P Perucca… - 2021 IEEE Signal …, 2021 - ieeexplore.ieee.org
Epilepsy diagnostic investigation involving manual visual analysis of electroencephalogram
(EEG) is a time-consuming process. Deep neural networks, especially the convolutional …
(EEG) is a time-consuming process. Deep neural networks, especially the convolutional …
Developing a deep learning based approach for anomalies detection from EEG data
Electroencephalography (EEG) contribute a leading role in brain studies, mental and brain
diseases and disorders diagnosis, and treatments. Traditional Machine Learning (TML) …
diseases and disorders diagnosis, and treatments. Traditional Machine Learning (TML) …
Nonconvulsive Seizure and Status Epilepticus Detection with Deep Learning in High-Risk Adult Critically Ill
J Tanlamai, A Pattanateepapon… - … Conference on Big …, 2022 - ieeexplore.ieee.org
Nonconvulsive seizure (NCS) is an electrographic seizure activity with subtle motor activity,
and prolonged NCS is nonconvulsive status epilepticus (NCSE). Their delayed treatment …
and prolonged NCS is nonconvulsive status epilepticus (NCSE). Their delayed treatment …
Task-oriented self-supervised learning for anomaly detection in electroencephalography
Accurate automated analysis of electroencephalography (EEG) would largely help clinicians
effectively monitor and diagnose patients with various brain diseases. Compared to …
effectively monitor and diagnose patients with various brain diseases. Compared to …
EMAP: A cloud-edge hybrid framework for EEG monitoring and cross-correlation based real-time anomaly prediction
BS Prabakaran, AG Jiménez… - 2020 57th ACM/IEEE …, 2020 - ieeexplore.ieee.org
State-of-the-art techniques for detecting, or predicting, neurological disorders (1) focus on
predicting each disorder individually, and are (2) computationally expensive, leading to a …
predicting each disorder individually, and are (2) computationally expensive, leading to a …
Improving Clinician Performance in Classifying EEG Patterns on the Ictal–Interictal Injury Continuum Using Interpretable Machine Learning
AJ Barnett, Z Guo, J Jing, W Ge, PW Kaplan, WY Kong… - NEJM AI, 2024 - ai.nejm.org
Background In intensive care units (ICUs), critically ill patients are monitored with
electroencephalography (EEG) to prevent serious brain injury. EEG monitoring is …
electroencephalography (EEG) to prevent serious brain injury. EEG monitoring is …
Anomaly detection in invasively recorded neuronal signals using deep neural network: effect of sampling frequency
Abnormality detection has advanced in recent years with the help of machine learning, in
particular with deep learning models, which can predict accurately across many types of …
particular with deep learning models, which can predict accurately across many types of …
An EEG abnormality detection algorithm based on graphic attention network
J Duan, F Xie, N Huang, N Luo, Z Guan, W Zhao… - Multimedia Tools and …, 2024 - Springer
The incidence of brain diseases has increased yearly, threatening human life and health
seriously. The Electroencephalogram (EEG) has been playing an important role in clinical …
seriously. The Electroencephalogram (EEG) has been playing an important role in clinical …
Anomaly detection in electroencephalography signal using deep learning model
S Tahura, SM Hasnat Samiul, M Shamim Kaiser… - … Conference on Trends …, 2021 - Springer
Biosignals such as Electroencephalogram (EEG), Electrocardiogram (ECG),
Electromyogram (EMG) represent the electrical activities of various parts of human body …
Electromyogram (EMG) represent the electrical activities of various parts of human body …