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A Multi-Model Unbiased Algorithm for Reliable Detection of Seizures
L Kamintsky
, I Weissberg
, M Ketzef
,
D Gitler
, A Becker
,
Y Zigel
,
A Friedman
Physiology and Cell Biology
Department of Biomedical Engineering
Research output
:
Contribution to conference
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Paper
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Dive into the research topics of 'A Multi-Model Unbiased Algorithm for Reliable Detection of Seizures'. Together they form a unique fingerprint.
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Keyphrases
Albumin
20%
Artificial Neural Network
20%
Artificial Neural Network Classification
20%
Classifier Training
20%
Computation Time
20%
Cortical Activity
20%
Electrocorticography (ECoG)
60%
Electroencephalography
20%
Epidural Electrode
20%
Epilepsy
20%
Epilepsy Patients
20%
Epileptic
20%
Feature Extraction
20%
Feature Subset
20%
Forward Selection
20%
Genetic Epilepsy
20%
Genetic Status
20%
Graphical User Interface
20%
Interictal Discharges
20%
Manual Inspection
20%
Mice Model of Epilepsy
20%
Multi-model
100%
Neurological Disorders
20%
Noise Artifacts
20%
Optimal Tradeoff
20%
Overall Sensitivity
20%
Performance Evaluation
20%
Positive Detection
20%
Positive Predictive Value
20%
Reliable Detection
100%
Reliable System
20%
Seizure
100%
Seizure Detection
20%
Selection Analysis
20%
Sliding Window
20%
Spontaneous Seizures
20%
Status Epilepticus
20%
System Performance
20%
Neuroscience
Albumin
33%
Artificial Neural Network
66%
Electrocorticography
100%
Electroencephalography
33%
Epilepsy
100%
Genetics
33%
Nervous System Disorder
33%
Status Epilepticus
33%