Drug resistance is estimated to affect about a third of individuals with epilepsy, but its
prevalence differs in relation to the epilepsy syndrome, the cause of epilepsy, and other …

Artificial Intelligence (AI) is a rapidly emerging technology in healthcare that has the
potential to revolutionise clinical nutrition. AI can assist in analysing complex data …

Electroencephalography (EEG) serves as a diagnostic technique for measuring brain waves
and brain activity. Despite its precision in capturing brain electrical activity, certain factors …

Abstract Purpose of Review Machine Learning (ML) and Artificial Intelligence (AI) are data-
driven techniques to translate raw data into applicable and interpretable insights that can …

Antiseizure medications (ASMs) are the mainstay of symptomatic epilepsy treatment. The
primary goal of pharmacotherapy with ASMs in epilepsy is to achieve complete seizure …

Over 65 million people suffer from recurrent, unprovoked seizures. The lack of validated
biomarkers specific for myriad forms of epilepsy makes diagnosis challenging. Diagnosis …

The current pace of development and applications of large language models (LLMs) is
unprecedented and will impact future medical care significantly. In this critical review, we …

Abstract Background and Objectives Understanding the multi-faceted treatment outcomes of
newly diagnosed epilepsy is critical for developing rational therapeutic strategies. A meta …

Background Clinical pharmacology research has always involved computational analysis.
With the abundance of drug-related data available, the integration of artificial intelligence …

Objectives To assess the temporal trends in the use of second antiseizure (ASM) regimens
and compare the efficacy of substitution monotherapy and combination therapy after failure …