Latest AI and machine learning research in seizures for healthcare professionals.
Accurate prediction of antiseizure medication (ASM) outcomes is crucial for optimising epilepsy treatment. We propose a multi-modal deep learning framework that integrates electroencephalography (EEG), magnetic resonance imaging (MRI), clinical factors, and molecular drug features to enhance ASM outcome prediction. Our approach includes EEG Q-Net, a pre-trained quantisation model capturing finegra...
To evaluate the potential of wrist-worn wearable devices to detect and quantify Faciobrachial Dystonic Seizures (FBDS) and related events associated with leucine-rich glioma Inactivated-1 (LGI1)-IgG autoimmune encephalitis (LGI1 AIE). Seven patients and four control subjects were monitored with Empatica E4 wristbands in both hospital and ambulatory environments. The analysis focused on the pre- an...
This study presents a novel computational approach for analyzing electroencephalogram (EEG) signals, focusing on the distribution and variability of e...
The neurological exam is pivotal in assessing patients with neurological conditions but has severe limitations: it can vary between examiners, it may ...
Sleep spindles, an oscillatory brain activity occurring during light non-rapid eye movement (NREM) sleep, are important for memory consolidation and c...
Recent advancements in signal processing techniques have enabled non-invasive Brain-Computer Interfaces (BCIs) to control assistive devices, like robo...
The objective of this study is to perform an independent assessment of the diagnostic utility of three state-of-the-art tools for the detection of foc...
Closed-loop neurostimulation is a promising treatment for drug-resistant focal epilepsy. A major challenge is fast and reliable seizure detection via ...
Accurate detection and classification of high-frequency oscillations (HFOs) in electroencephalography (EEG) recordings have become increasingly import...
Major depressive disorder (MDD) is a heterogeneous neuropsychiatric disorder with highly variable antidepressant outcomes. In randomized controlled tr...
Bottom-of-sulcus dysplasia (BOSD) is a diagnostically challenging subtype of focal cortical dysplasia, 60% being missed on patients’ first MRI. Automa...
Rapid Eye Movement (REM) Sleep Behavior Disorder (RBD) is a parasomnia characterized by the loss of physiological muscle atonia during REM sleep, ofte...
MRI is critical for the detection of subtle cortical pathology in epilepsy surgery assessment. This can be aided by improved MRI quality and resolutio...
Recently, automated Interictal Epileptiform Discharge (IED) detection has attracted significant attention as a challenging predictive data analysis ta...
Fragile X Syndrome (FXS) is a rare neurodevelopmental disorder caused by a trinucleotide repeat expansion on the 5’ untranslated region of the FMR1 ge...
The goal of this scoping review is to review the scope of features from previous resting-state electroencephalography (EEG) research that have the pot...
Understanding the relevance of covert cerebrovascular disease (CCD) for later health will allow clinicians to more effectively monitor and target inte...
Chronic pain impacts more than one in five adults in the United States (US) and the costs associated with the condition amount to hundreds of billions...
Precision-guided dual antiplatelet therapy (DAPT) duration post-percutaneous coronary intervention (PCI) remains a clinical challenge. Current risk st...
Epilepsy is a neurological disorder that affects approximately 1% of the global population. The current method for seizure monitoring, seizure diaries...