AIMC Topic: Anticonvulsants
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How accurate are machine learning models in predicting anti-seizure medication responses: A systematic review.
Epilepsy & behavior : E&B
Dec 13, 2024
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...
Machine learning models for predicting treatment response in infantile epilepsies.
Epilepsy & behavior : E&B
Oct 10, 2024
UNLABELLED: Epilepsy stands as one of the prevalent and significant neurological disorders, representing a critical healthcare challenge. Recently, machine learning techniques have emerged as versatile tools across various healthcare domains, encompa...
OxcarNet: sinc convolutional network with temporal and channel attention for prediction of oxcarbazepine monotherapy responses in patients with newly diagnosed epilepsy.
Journal of neural engineering
Sep 19, 2024
Monotherapy with antiepileptic drugs (AEDs) is the preferred strategy for the initial treatment of epilepsy. However, an inadequate response to the initially prescribed AED is a significant indicator of a poor long-term prognosis, emphasizing the imp...
Joint use of population pharmacokinetics and machine learning for prediction of valproic acid plasma concentration in elderly epileptic patients.
European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
Aug 10, 2024
BACKGROUND: Valproic acid (VPA) is a commonly used broad-spectrum antiepileptic drug. For elderly epileptic patients, VPA plasma concentrations have a considerable variation. We aim to establish a prediction model via a combination of machine learnin...
In Silico drug repurposing pipeline using deep learning and structure based approaches in epilepsy.
Scientific reports
Jul 17, 2024
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 ...
Predicting efficacy of antiseizure medication treatment with machine learning algorithms in North Indian population.
Epilepsy research
Jul 1, 2024
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 automatic machine learning model to predict abnormal increase of transaminase in valproic acid-treated epilepsy.
Archives of toxicology
Jun 16, 2024
Valproic acid (VPA) is a primary medication for epilepsy, yet its hepatotoxicity consistently raises concerns among individuals. This study aims to establish an automated machine learning (autoML) model for forecasting the risk of abnormal increase o...
A computational clinical decision-supporting system to suggest effective anti-epileptic drugs for pediatric epilepsy patients based on deep learning models using patient's medical history.
BMC medical informatics and decision making
May 31, 2024
BACKGROUND: Epilepsy, a chronic brain disorder characterized by abnormal brain activity that causes seizures and other symptoms, is typically treated using anti-epileptic drugs (AEDs) as the first-line therapy. However, due to the variations in their...
Quercetin Exerts Anticonvulsant Effect through Mitigation of Neuroinflammatory Response in Pentylenetetrazole-induced Seizure in Mice.
Nigerian journal of physiological sciences : official publication of the Physiological Society of Nigeria
Dec 31, 2023
Epilepsy is a chronic disease of the brain characterized by seizures. The currently available anticonvulsants only treat symptoms with serious adverse drug reactions. Therefore, there is need for new therapeutic intervention that will prevent epilept...
Impaired phase synchronization of motor-evoked potentials reflects the degree of motor dysfunction in the lesioned human brain.
Human brain mapping
Feb 24, 2022
The functional corticospinal integrity (CSI) can be indexed by motor-evoked potentials (MEP) following transcranial magnetic stimulation of the motor cortex. Glial brain tumors in motor-eloquent areas are frequently disturbing CSI resulting in differ...
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