AIMC Topic: Epilepsy

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A data augmentation procedure to improve detection of spike ripples in brain voltage recordings.

Neuroscience research
Epilepsy is a major neurological disorder characterized by recurrent, spontaneous seizures. For patients with drug-resistant epilepsy, treatments include neurostimulation or surgical removal of the epileptogenic zone (EZ), the brain region responsibl...

A novel universal deep learning approach for accurate detection of epilepsy.

Medical engineering & physics
Epilepsy claims the lives of many people, so researchers strive to build highly accurate diagnostic models. One of the limitations of obtaining high accuracy is the scarcity of Electroencephalography (EEG) data and the fact that they are from differe...

A scheme combining feature fusion and hybrid deep learning models for epileptic seizure detection and prediction.

Scientific reports
Epilepsy is one of the most well-known neurological disorders globally, leading to individuals experiencing sudden seizures and significantly impacting their quality of life. Hence, there is an urgent necessity for an efficient method to detect and p...

In Silico drug repurposing pipeline using deep learning and structure based approaches in epilepsy.

Scientific reports
Due to considerable global prevalence and high recurrence rate, the pursuit of effective new medication for epilepsy treatment remains an urgent and significant challenge. Drug repurposing emerges as a cost-effective and efficient strategy to combat ...

Automatic diagnosis of epileptic seizures using entropy-based features and multimodel deep learning approaches.

Medical engineering & physics
Epilepsy is one of the most common brain diseases, characterised by repeated seizures that occur on a regular basis. During a seizure, a patient's muscles flex uncontrollably, causing a loss of mobility and balance, which can be harmful or even fatal...

SMARTSeiz: Deep Learning With Attention Mechanism for Accurate Seizure Recognition in IoT Healthcare Devices.

IEEE journal of biomedical and health informatics
The Internet of Things (IoT) is capable of controlling the healthcare monitoring system for remote-based patients. Epilepsy, a chronic brain syndrome characterized by recurrent, unpredictable attacks, affects individuals of all ages. IoT-based seizur...

Predicting efficacy of antiseizure medication treatment with machine learning algorithms in North Indian population.

Epilepsy research
PURPOSE: This study aimed to develop a classifier using supervised machine learning to effectively assess the impact of clinical, demographical, and biochemical factors in accurately predicting the antiseizure medications (ASMs) treatment response in...

Development and validation of an interpretable machine learning model for predicting post-stroke epilepsy.

Epilepsy research
BACKGROUND: Epilepsy is a serious complication after an ischemic stroke. Although two studies have developed prediction model for post-stroke epilepsy (PSE), their accuracy remains insufficient, and their applicability to different populations is unc...

Speech decoding from stereo-electroencephalography (sEEG) signals using advanced deep learning methods.

Journal of neural engineering
Brain-computer interfaces (BCIs) are technologies that bypass damaged or disrupted neural pathways and directly decode brain signals to perform intended actions. BCIs for speech have the potential to restore communication by decoding the intended spe...