AIMC Topic: Electroencephalography
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Cross-Domain Classification Model With Knowledge Utilization Maximization for Recognition of Epileptic EEG Signals.
IEEE/ACM transactions on computational biology and bioinformatics
Feb 3, 2021
Conventional classification models for epileptic EEG signal recognition need sufficient labeled samples as training dataset. In addition, when training and testing EEG signal samples are collected from different distributions, for example, due to dif...
Validation of a Machine Learning Brain Electrical Activity-Based Index to Aid in Diagnosing Concussion Among Athletes.
JAMA network open
Feb 1, 2021
IMPORTANCE: An objective, reliable indicator of the presence and severity of concussive brain injury and of the readiness for the return to activity has the potential to reduce concussion-related disability.
Deep Learning for EEG Seizure Detection in Preterm Infants.
International journal of neural systems
Jan 30, 2021
EEG is the gold standard for seizure detection in the newborn infant, but EEG interpretation in the preterm group is particularly challenging; trained experts are scarce and the task of interpreting EEG in real-time is arduous. Preterm infants are re...
Machine learning approaches reveal subtle differences in breathing and sleep fragmentation in -derived astrocytes ablated mice.
Journal of neurophysiology
Jan 27, 2021
Modern neurophysiology research requires the interrogation of high-dimensionality data sets. Machine learning and artificial intelligence (ML/AI) workflows have permeated into nearly all aspects of daily life in the developed world but have not been ...
Machine Learning Techniques for Personalized Detection of Epileptic Events in Clinical Video Recordings.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Jan 25, 2021
Continuous patient monitoring is essential to achieve an effective and optimal patient treatment in the intensive care unit. In the specific case of epilepsy it is the only way to achieve a correct diagnosis and a subsequent optimal medication plan i...
Machine Learning for Predicting Epileptic Seizures Using EEG Signals: A Review.
IEEE reviews in biomedical engineering
Jan 22, 2021
With the advancement in artificial intelligence (AI) and machine learning (ML) techniques, researchers are striving towards employing these techniques for advancing clinical practice. One of the key objectives in healthcare is the early detection and...
A Review on Machine Learning for EEG Signal Processing in Bioengineering.
IEEE reviews in biomedical engineering
Jan 22, 2021
Electroencephalography (EEG) has been a staple method for identifying certain health conditions in patients since its discovery. Due to the many different types of classifiers available to use, the analysis methods are also equally numerous. In this ...
Frontotemporal EEG to guide sedation in COVID-19 related acute respiratory distress syndrome.
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
Jan 20, 2021
OBJECTIVE: To study if limited frontotemporal electroencephalogram (EEG) can guide sedation changes in highly infectious novel coronavirus disease 2019 (COVID-19) patients receiving neuromuscular blocking agent.
Preictal state detection using prodromal symptoms: A machine learning approach.
Epilepsia
Jan 19, 2021
A reliable identification of a high-risk state for upcoming seizures may allow for preemptive treatment and improve the quality of patients' lives. We evaluated the ability of prodromal symptoms to predict preictal states using a machine learning (ML...
Reading
Drug Resistant Epilepsy
Prodromal Symptoms
Photophobia
Affect
Comprehension
Hearing Loss
Noise
Area Under Curve
Electroencephalography
Seizures
Attention
Video Recording
Tinnitus
Speech
Surveys and Questionnaires
Support Vector Machine
Vision Disorders
Adult
Male
Middle Aged
Humans
Machine Learning
Female
Young Adult
Detection of Epileptic Seizure Using Pretrained Deep Convolutional Neural Network and Transfer Learning.
European neurology
Jan 8, 2021
INTRODUCTION: The diagnosis of epilepsy takes a certain process, depending entirely on the attending physician. However, the human factor may cause erroneous diagnosis in the analysis of the EEG signal. In the past 2 decades, many advanced signal pro...
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