IMPORTANCE: Current epilepsy management protocols often depend on anti-seizure medication (ASM) trials and assessment of clinical response. This may delay the initiation of the ASM regimen that might optimally balance efficacy and tolerability for in...
BACKGROUND: Real-time monitoring of pediatric epileptic seizures poses a significant challenge in clinical practice. In recent years, machine learning (ML) has attracted substantial attention from researchers for diagnosing and treating neurological ...
Biomedical physics & engineering express
Dec 11, 2024
The prediction of epileptic seizures is a classical research problem, representing one of the most challenging tasks in the analysis of brain disorders. There is active research into digital twins (DT) for various healthcare applications, as they can...
PURPOSE: This study aims to evaluate the similarity, readability, and alignment with current scientific knowledge of responses from AI-based chatbots to common questions about epilepsy and physical exercise.
BACKGROUND: Post-stroke epilepsy (PSE) is a critical complication that worsens both prognosis and quality of life in patients with ischemic stroke. An interpretable machine learning model was developed to predict PSE using medical records from four h...
OBJECTIVE: Deep learning methods have shown potential in automating the detection of interictal epileptiform discharges (IEDs) in electroencephalography (EEG). We compared IED detection using our previously trained deep neural network with a group of...
. Accurate and timely prediction of epileptic seizures is crucial for empowering patients to mitigate their impact or prevent them altogether. Current studies predominantly focus on short-term seizure predictions, which causes the prediction time to ...
Neural networks : the official journal of the International Neural Network Society
Oct 28, 2024
Timely detecting epileptic seizures can significantly reduce accidental injuries of epilepsy patients and offer a novel intervention approach to improve their quality of life. Investigation on seizure detection based on deep learning models has achie...
OBJECTIVE: Recently, we developed a first artificial intelligence (AI)-based digital pathology classifier for focal cortical dysplasia (FCD) as defined by the ILAE classification. Herein, we tested the usefulness of the classifier in a retrospective ...
Epileptic seizure prediction plays a crucial role in enhancing the quality of life for individuals with epilepsy. Over recent years, a multitude of deep learning-based approaches have emerged to tackle this challenging task, leading to significant ad...
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