Artificial intelligence for clinical decision support in neurology

M Pedersen, K Verspoor, M Jenkinson… - Brain …, 2020 - academic.oup.com
Artificial intelligence is one of the most exciting methodological shifts in our era. It holds the
potential to transform healthcare as we know it, to a system where humans and machines …

[HTML][HTML] Epileptic multi-seizure type classification using electroencephalogram signals from the Temple University Hospital Seizure Corpus: A review

N McCallan, S Davidson, KY Ng, P Biglarbeigi… - Expert Systems with …, 2023 - Elsevier
Epilepsy is one of the most paramount neurological diseases, affecting about 1% of the
world's population. Seizure detection and classification are difficult tasks and are ongoing …

Semi-dilated convolutional neural networks for epileptic seizure prediction

R Hussein, S Lee, R Ward, MJ McKeown - Neural Networks, 2021 - Elsevier
Epilepsy is a neurological brain disorder that affects∼ 75 million people worldwide.
Predicting epileptic seizures holds great potential for improving the quality of life of people …

Multi-channel vision transformer for epileptic seizure prediction

R Hussein, S Lee, R Ward - Biomedicines, 2022 - mdpi.com
Epilepsy is a neurological disorder that causes recurrent seizures and sometimes loss of
awareness. Around 30% of epileptic patients continue to have seizures despite taking anti …

An overview of EEG-based machine learning methods in seizure prediction and opportunities for neurologists in this field

B Maimaiti, H Meng, Y Lv, J Qiu, Z Zhu, Y Xie, Y Li… - Neuroscience, 2022 - Elsevier
The unpredictability of epileptic seizures is one of the most problematic aspects of the field of
epilepsy. Methods or devices capable of detecting seizures minutes before they occur may …

New advances in pharmacoresistant epilepsy towards precise management-from prognosis to treatments

C Xu, Y Gong, Y Wang, Z Chen - Pharmacology & Therapeutics, 2022 - Elsevier
Epilepsy, one of the most severe neurological diseases, is characterized by abrupt recurrent
seizures. Despite great progress in the development of antiseizure drugs (ASDs) based on …

Deep learning for EEG seizure detection in preterm infants

A O'Shea, R Ahmed, G Lightbody… - … journal of neural …, 2021 - World Scientific
EEG is the gold standard for seizure detection in the newborn infant, but EEG interpretation
in the preterm group is particularly challenging; trained experts are scarce and the task of …

Epileptic seizure prediction using spectral width of the covariance matrix

D EPMoghaddam, SA Sheth, Z Haneef… - Journal of Neural …, 2022 - iopscience.iop.org
Objective. Epilepsy is a common neurological disorder in which patients suffer from sudden
and unpredictable seizures. Seizures are caused by excessive and abnormal neuronal …

An efficient epilepsy prediction model on european dataset with model evaluation considering seizure types

SM Varnosfaderani, I McNulty… - IEEE Journal of …, 2024 - ieeexplore.ieee.org
This paper develops a computationally efficient model for automatic patient-specific seizure
prediction using a two-layer LSTM from multichannel intracranial electroencephalogram …

Prediction of seizure recurrence. A note of caution

WJ Bosl, A Leviton, T Loddenkemper - Frontiers in Neurology, 2021 - frontiersin.org
Great strides have been made recently in documenting that machine-learning programs can
predict seizure occurrence in people who have epilepsy. Along with this progress have …