AIMC Topic: Epilepsy

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2D Wavelet-Scalogram Deep-Learning for Seizures Pattern Identification in the Post-Hypoxic-Ischemic EEG of Preterm Fetal Sheep.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Neonatal seizures after an hypoxic-ischemic (HI) event in preterm newborns can contribute to neural injury and cause impaired brain development. Preterm neonatal seizures are often not detected or their occurrence underestimated. Therefore, there is ...

Real-Time Epileptic Seizure Detection Based on Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Epilepsy is one of the most common neurological diseases, and video EEG is the most commonly used examination method for epilepsy diagnosis. However, since the video EEG examination lasts for hours, the escort has a heavy burden, and the large amount...

A Self-Interpretable Deep Learning Model for Seizure Prediction Using a Multi-Scale Prototypical Part Network.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
The epileptic seizure prediction (ESP) method aims to timely forecast the occurrence of seizures, which is crucial to improving patients' quality of life. Many deep learning-based methods have been developed to tackle this issue and achieve significa...

Artificial Intelligence-based Detection of Epileptic Discharges from Pediatric Scalp Electroencephalograms: A Pilot Study.

Acta medica Okayama
We developed an artificial intelligence (AI) technique to identify epileptic discharges (spikes) in pediatric scalp electroencephalograms (EEGs). We built a convolutional neural network (CNN) model to automatically classify steep potential images int...

Development and Validation of a Deep Learning Model for Predicting Treatment Response in Patients With Newly Diagnosed Epilepsy.

JAMA neurology
IMPORTANCE: Selection of antiseizure medications (ASMs) for epilepsy remains largely a trial-and-error approach. Under this approach, many patients have to endure sequential trials of ineffective treatments until the "right drugs" are prescribed.

Classification of Seizure Termination Patterns using Deep Learning on intracranial EEG.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Seizure termination has received significantly less attention than initiation and propagation and consequently, remains a poorly understood phase of seizure evolution. Yet, its study may have a significant impact on the development of efficient inter...

[Epilepsy detection and analysis method for specific patient based on data augmentation and deep learning].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
In recent years, epileptic seizure detection based on electroencephalogram (EEG) has attracted the widespread attention of the academic. However, it is difficult to collect data from epileptic seizure, and it is easy to cause over fitting phenomenon ...

Extracting seizure frequency from epilepsy clinic notes: a machine reading approach to natural language processing.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Seizure frequency and seizure freedom are among the most important outcome measures for patients with epilepsy. In this study, we aimed to automatically extract this clinical information from unstructured text in clinical notes. If success...

Seizure Type Classification Using EEG Based on Gramian Angular Field Transformation and Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
classification of seizure types plays a crucial role in diagnosis and prognosis of epileptic patients which has not been addressed properly, while most of the works are surrounded by seizure detection only. However, in recent times, few works have be...