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Seizures

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Artificial intelligence/machine learning for epilepsy and seizure diagnosis.

Epilepsy & behavior : E&B
Accurate seizure and epilepsy diagnosis remains a challenging task due to the complexity and variability of manifestations, which can lead to delayed or missed diagnosis. Machine learning (ML) and artificial intelligence (AI) is a rapidly developing ...

Attention-based deep convolutional neural network for classification of generalized and focal epileptic seizures.

Epilepsy & behavior : E&B
Epilepsy affects over 50 million people globally. Electroencephalography is critical for epilepsy diagnosis, but manual seizure classification is time-consuming and requires extensive expertise. This paper presents an automated multi-class seizure cl...

Deep learning approaches for seizure video analysis: A review.

Epilepsy & behavior : E&B
Seizure events can manifest as transient disruptions in the control of movements which may be organized in distinct behavioral sequences, accompanied or not by other observable features such as altered facial expressions. The analysis of these clinic...

A hybrid EEG classification model using layered cascade deep learning architecture.

Medical & biological engineering & computing
The problem of multi-class classification is always a challenge in the field of EEG (electroencephalogram)-based seizure detection. The traditional studies focus on computing or learning a set of features from EEG to distinguish between different pat...

A comparative study of CNN-capsule-net, CNN-transformer encoder, and Traditional machine learning algorithms to classify epileptic seizure.

BMC medical informatics and decision making
INTRODUCTION: Epilepsy is a disease characterized by an excessive discharge in neurons generally provoked without any external stimulus, known as convulsions. About 2 million people are diagnosed each year in the world. This process is carried out by...

Biomimetic Deep Learning Networks With Applications to Epileptic Spasms and Seizure Prediction.

IEEE transactions on bio-medical engineering
OBJECTIVE: In this study, we present a novel biomimetic deep learning network for epileptic spasms and seizure prediction and compare its performance with state-of-the-art conventional machine learning models.

Quercetin Exerts Anticonvulsant Effect through Mitigation of Neuroinflammatory Response in Pentylenetetrazole-induced Seizure in Mice.

Nigerian journal of physiological sciences : official publication of the Physiological Society of Nigeria
Epilepsy is a chronic disease of the brain characterized by seizures. The currently available anticonvulsants only treat symptoms with serious adverse drug reactions. Therefore, there is need for new therapeutic intervention that will prevent epilept...

Using Explainable Artificial Intelligence to Obtain Efficient Seizure-Detection Models Based on Electroencephalography Signals.

Sensors (Basel, Switzerland)
Epilepsy is a condition that affects 50 million individuals globally, significantly impacting their quality of life. Epileptic seizures, a transient occurrence, are characterized by a spectrum of manifestations, including alterations in motor functio...

An overview of machine learning and deep learning techniques for predicting epileptic seizures.

Journal of integrative bioinformatics
Epilepsy is a neurological disorder (the third most common, following stroke and migraines). A key aspect of its diagnosis is the presence of seizures that occur without a known cause and the potential for new seizures to occur. Machine learning has ...

Detection and classification of adult epilepsy using hybrid deep learning approach.

Scientific reports
The electroencephalogram (EEG) has emerged over the past few decades as one of the key tools used by clinicians to detect seizures and other neurological abnormalities of the human brain. The proper diagnosis of epilepsy is crucial due to its distinc...