ArticleEpilepsia2012
Automated diagnosis of epilepsy using EEG power spectrum.
Article in Epilepsia, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
20 citing papers in PubMed, 1 synthesis or guideline pooled it, 35 citations in OpenAlex.
- Bring on the Machines: Could Machine Learning Improve the Quality of Patient Education Materials? A Systematic Search and Rapid Review.JCO clinical cancer informatics · 2018Pooled it
- Diagnosing Epilepsy with Normal Interictal EEG Using Dynamic Network Models.Annals of neurology · 2025Article
- Supervised machine learning compared to large language models for identifying functional seizures from medical records.Epilepsia · 2025Article
- The present and future of seizure detection, prediction, and forecasting with machine learning, including the future impact on clinical trials.Frontiers in neurology · 2024Review
- Machine Learning and Artificial Intelligence Applications to Epilepsy: a Review for the Practicing Epileptologist.Current neurology and neuroscience reports · 2023Review
- Can Presurgical Interhemispheric EEG Connectivity Predict Outcome in Hemispheric Surgery? A Brain Machine Learning Approach.Brain sciences · 2022Article
- Neural Decoding of EEG Signals with Machine Learning: A Systematic Review.Brain sciences · 2021Review
- Article
- Validation of a predictive calculator to distinguish between patients presenting with dissociative versus epileptic seizures.Epilepsy & behavior : E&B · 2021Article
- Article
- Objective score from initial interview identifies patients with probable dissociative seizures.Epilepsy & behavior : E&B · 2020Article
- An objective score to identify psychogenic seizures based on age of onset and history.Epilepsy & behavior : E&B · 2018Article
- Article
- Diagnostic implications of review-of-systems questionnaires to differentiate epileptic seizures from psychogenic seizures.Epilepsy & behavior : E&B · 2017Article
- Diagnostic delay in psychogenic seizures and the association with anti-seizure medication trials.Seizure · 2016Article
- Interval analysis of interictal EEG: pathology of the alpha rhythm in focal epilepsy.Scientific reports · 2015Article
- Multimodal data and machine learning for surgery outcome prediction in complicated cases of mesial temporal lobe epilepsy.Computers in biology and medicine · 2015Article
- Multimodal diagnosis of epilepsy using conditional dependence and multiple imputation.... International Workshop on Pattern Recognition in NeuroImaging. International Workshop on Pattern Recognition in NeuroImaging · 2014Article
- Balancing Clinical and Pathologic Relevence in the Machine Learning Diagnosis of Epilepsy.... International Workshop on Pattern Recognition in NeuroImaging. International Workshop on Pattern Recognition in NeuroImaging · 2013Article
- Computer-Aided Diagnosis and Localization of Lateralized Temporal Lobe Epilepsy Using Interictal FDG-PET.Frontiers in neurology · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 1 institution in 1 country.
Funding
Abstract
Interictal electroencephalography (EEG) has clinically meaningful limitations in its sensitivity and specificity in the diagnosis of epilepsy because of its dependence on the occurrence of epileptiform discharges. We have developed a computer-aided diagnostic (CAD) tool that operates on the absolute spectral energy of the routine EEG and has both substantially higher sensitivity and negative predictive value than the identification of interictal epileptiform discharges. Our approach used a multilayer perceptron to classify 156 patients admitted for video-EEG monitoring. The patient population was diagnostically diverse; 87 were diagnosed with either generalized or focal seizures. The remainder of the patients were diagnosed with nonepileptic seizures. The sensitivity was 92% (95% confidence interval [CI] 85-97%) and the negative predictive value was 82% (95% CI 67-92%). We discuss how these findings suggest that this CAD can be used to supplement event-based analysis by trained epileptologists.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.