AIMC Topic: Seizures

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Towards Improved Design and Evaluation of Epileptic Seizure Predictors.

IEEE transactions on bio-medical engineering May 2, 2017
OBJECTIVE: Key issues in the epilepsy seizure prediction research are (1) the reproducibility of results (2) the inability to compare multiple approaches directly. To overcome these problems, the seizure prediction challenge was organized on Kaggle.c...
Discriminant Analysis Electroencephalography Seizures Signal Processing, Computer-Assisted Humans Neural Networks, Computer Support Vector Machine Models, Statistical
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Recurring Functional Interactions Predict Network Architecture of Interictal and Ictal States in Neocortical Epilepsy.

eNeuro Mar 8, 2017
Human epilepsy patients suffer from spontaneous seizures, which originate in brain regions that also subserve normal function. Prior studies demonstrate focal, neocortical epilepsy is associated with dysfunction, several hours before seizures. How do...
Male Time Factors Cluster Analysis Models, Neurological Humans Female Drug Resistant Epilepsy Electrocorticography Electrodes, Implanted Neocortex Unsupervised Machine Learning Brain Mapping Seizures Datasets as Topic
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Machine learning-based prediction of adverse drug effects: An example of seizure-inducing compounds.

Journal of pharmacological sciences Jan 28, 2017
Various biological factors have been implicated in convulsive seizures, involving side effects of drugs. For the preclinical safety assessment of drug development, it is difficult to predict seizure-inducing side effects. Here, we introduced a machin...
CA1 Region, Hippocampal Support Vector Machine Animals Mice, Inbred ICR Male Theophylline Seizures In Vitro Techniques Enoxacin Diphenhydramine Mice Strychnine
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Automated seizure detection using limited-channel EEG and non-linear dimension reduction.

Computers in biology and medicine Jan 25, 2017
Electroencephalography (EEG) is an essential component in evaluation of epilepsy. However, full-channel EEG signals recorded from 18 to 23 electrodes on the scalp is neither wearable nor computationally effective. This paper presents advantages of bo...
Humans Electroencephalography Machine Learning Seizures Algorithms Nonlinear Dynamics Reproducibility of Results Pattern Recognition, Automated Sensitivity and Specificity Diagnosis, Computer-Assisted Sample Size Data Interpretation, Statistical
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A Realistic Seizure Prediction Study Based on Multiclass SVM.

International journal of neural systems Sep 23, 2016
A patient-specific algorithm, for epileptic seizure prediction, based on multiclass support-vector machines (SVM) and using multi-channel high-dimensional feature sets, is presented. The feature sets, combined with multiclass classification and post-...
Seizures Support Vector Machine Europe Electroencephalography Epilepsy Middle Aged Adolescent Child, Preschool Child Precision Medicine Prognosis Female Aged Young Adult Humans Adult Databases, Factual Sensitivity and Specificity Prospective Studies Male Brain
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LMD Based Features for the Automatic Seizure Detection of EEG Signals Using SVM.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Sep 20, 2016
Achieving the goal of detecting seizure activity automatically using electroencephalogram (EEG) signals is of great importance and significance for the treatment of epileptic seizures. To realize this aim, a newly-developed time-frequency analytical ...
Seizures Pattern Recognition, Automated Humans Algorithms Reproducibility of Results Sensitivity and Specificity Diagnosis, Computer-Assisted Support Vector Machine Electroencephalography
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Seizure Forecasting and the Preictal State in Canine Epilepsy.

International journal of neural systems Jun 14, 2016
The ability to predict seizures may enable patients with epilepsy to better manage their medications and activities, potentially reducing side effects and improving quality of life. Forecasting epileptic seizures remains a challenging problem, but ma...
Animals Time Factors ROC Curve Disease Models, Animal Area Under Curve Epilepsy Seizures Signal Processing, Computer-Assisted Machine Learning Prognosis Dogs Electrocorticography Wireless Technology Electrodes, Implanted
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Statistical Performance Analysis of Data-Driven Neural Models.

International journal of neural systems Jun 9, 2016
Data-driven model-based analysis of electrophysiological data is an emerging technique for understanding the mechanisms of seizures. Model-based analysis enables tracking of hidden brain states that are represented by the dynamics of neural mass mode...
Humans Models, Neurological Data Interpretation, Statistical Bayes Theorem Epilepsy Neural Networks, Computer Uncertainty Algorithms Brain Membrane Potentials Computer Simulation Seizures Neurons Synapses Stochastic Processes
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Validation of a novel classification model of psychogenic nonepileptic seizures by video-EEG analysis and a machine learning approach.

Epilepsy & behavior : E&B May 20, 2016
The aim of this study was to validate a novel classification for the diagnosis of PNESs. Fifty-five PNES video-EEG recordings were retrospectively analyzed by four epileptologists and one psychiatrist in a blind manner and classified into four distin...
Video Recording Diagnosis, Differential Focus Groups Single-Blind Method Somatoform Disorders Electroencephalography Seizures Retrospective Studies Female Male Middle Aged Humans Neural Networks, Computer Machine Learning Psychiatry
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An Improved Sparse Representation over Learned Dictionary Method for Seizure Detection.

International journal of neural systems Sep 14, 2015
Automatic seizure detection has played an important role in the monitoring, diagnosis and treatment of epilepsy. In this paper, a patient specific method is proposed for seizure detection in the long-term intracranial electroencephalogram (EEG) recor...
Humans Sensitivity and Specificity Neural Networks, Computer Predictive Value of Tests Algorithms Electroencephalography Seizures
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