ArticleHealth information science and systems2020
Automated epilepsy detection techniques from electroencephalogram signals: a review study.
Article in Health information science and systems, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
31 citing papers in PubMed, 101 citations in OpenAlex.
- A time-frequency cross-attention network model for epileptic seizure detection.Scientific reports · 2026Article
- TFFBN-HDLF: a hybrid deep learning framework based on time-frequency functional brain networks for epileptic seizure detection.Frontiers in medicine · 2026Article
- CONECT: Novel Weighted Networks Framework Leveraging Angle-Relation Connection (ARC) and Metaheuristic Algorithms for EEG-Based Dementia Classification.Sensors (Basel, Switzerland) · 2025Article
- A deep hybrid CSAE-GRU framework with two-stage balancing for automatic epileptic seizure detection using EEG-derived features.Frontiers in neuroscience · 2025Article
- Automatic detection and prediction of epileptic EEG signals based on nonlinear dynamics and deep learning: a review.Frontiers in neuroscience · 2025Review
- Computer-assisted analysis of routine EEG to identify hidden biomarkers of epilepsy: A systematic review.Computational and structural biotechnology journal · 2024Review
- A multi-source heterogeneous medical data enhancement framework based on lakehouse.Health information science and systems · 2024Article
- Theta-gamma-coupling as predictor of working memory performance in young and elderly healthy people.Molecular brain · 2024Article
- Improving working memory by electrical stimulation and cross-frequency coupling.Molecular brain · 2024Article
- Automatic detection of epilepsy from EEGs using a temporal convolutional network with a self-attention layer.Biomedical engineering online · 2024Article
- The value of linear and non-linear quantitative EEG analysis in paediatric epilepsy surgery: a machine learning approach.Scientific reports · 2024Article
- Efficient novel network and index for alcoholism detection from EEGs.Health information science and systems · 2023Article
- Using nutrigenomics to guide personalized nutrition supplementation for bolstering immune system.Health information science and systems · 2023Article
- The nnU-Net based method for automatic segmenting fetal brain tissues.Health information science and systems · 2023Article
- Patient assignment optimization in cloud healthcare systems: a distributed genetic algorithm.Health information science and systems · 2023Article
- Effectiveness assessment of repetitive transcranial alternating current stimulation with concurrent EEG and fNIRS measurement.Health information science and systems · 2023Article
- Epileptic EEG Signal Detection Using Variational Modal Decomposition and Improved Grey Wolf Algorithm.Sensors (Basel, Switzerland) · 2023Article
- Computer-assisted analysis of routine electroencephalogram to identify hidden biomarkers of epilepsy: protocol for a systematic review.BMJ open · 2023Article
- Study on characteristic of epileptic multi-electroencephalograph base on Hilbert-Huang transform and brain network dynamics.Frontiers in neuroscience · 2023Article
- Identifying informative tweets during a pandemic via a topic-aware neural language model.World wide web · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Epilepsy is a serious neurological condition which contemplates as top 5 reasons for avoidable mortality from ages 5-29 in the worldwide. The avoidable deaths due to epilepsy can be reduced by developing efficient automated epilepsy detection or prediction machines or software. To develop an automated epilepsy detection framework, it is essential to properly understand the existing techniques and their benefit as well as detriment also. This paper aims to provide insight on the information about the existing epilepsy detection and classification techniques as they are crucial for supporting clinical-decision in the course of epilepsy treatment. This review study accentuate on the existing epilepsy detection approaches and their drawbacks. This information presented in this article will be helpful to the neuroscientist, researchers as well as to technicians for assisting them in selecting the reliable and appropriate techniques for analyzing epilepsy and developing an automated software system of epilepsy identification.
Indexed as
Identifiers
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.