SOTAVerified|Agents Browse Leaderboard About

Seizure Detection

Seizure Detection is a binary supervised classification problem with the aim of classifying between seizure and non-seizure states of a patient.

Source: ResOT: Resource-Efficient Oblique Trees for Neural Signal Classification

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 171–175 of 175 papers

Title	Date	Tasks	Status	Hype
Learning Robust Features using Deep Learning for Automatic Seizure Detection	Jul 31, 2016	Deep LearningEEG	CodeCode Available	0
A Compressed Sensing Based Decomposition of Electrodermal Activity Signals	Feb 24, 2016	compressed sensingSeizure Detection	—Unverified	0
A Novel Matrix Representation of Discrete Biomedical Signals	Jan 13, 2016	Seizure Detection	—Unverified	0
An Open-source Toolbox for Analysing and Processing PhysioNet Databases in MATLAB and Octave	Sep 24, 2014	Arrhythmia DetectionEEG	CodeCode Available	0
Fast SVM training using approximate extreme points	Apr 4, 2013	General ClassificationSeizure Detection	—Unverified	0

Show:10 25 50

← PrevPage 18 of 18Next →

All datasets TUH EEG Seizure Corpus CHB-MIT

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	ResNet+ LSTM	AUROC	0.92	—	Unverified
2	CNN2D+LSTM	AUROC	0.92	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	TF-Tensor-CNN	Accuracy	89.63	—	Unverified