Artificial intelligence (AI) is rapidly transforming health care, and its applications in epilepsy
have increased exponentially over the past decade. Integration of AI into epilepsy …

Background Systemic diseases, such as cardiovascular and cerebrovascular conditions,
pose significant global health challenges due to their high mortality rates. Early identification …

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 …

Psychiatric disorders are highly comorbid, heritable, and genetically correlated [,,–]. The
primary objective of cross-disorder psychiatric genetics research is to identify and …

Epilepsy is a natural target for studying clinical prediction. The condition is characterised by
a lasting predisposition to spontaneous seizures. 2 The point at which a person is defined …

Forecasting the short-term spread of an ongoing disease outbreak is a formidable challenge
due to the complexity of contributing factors, some of which can be characterized through …

We fill a gap in scholarship by applying a generative Large Language Model (LLM) to
extract information from clinical free text about the frequency of seizures experienced by …

Seizure recurrence is an important concern after an initial unprovoked seizure; without drug
treatment, it occurs within 2 years in 40-50% of cases. The decision to treat currently relies …

Background and Objectives: The diagnostic yield of routine EEG in epilepsy is limited by low
sensitivity and the potential for misinterpretation of interictal epileptiform discharges (IEDs) …

Objective: Accurate and timely epilepsy diagnosis is crucial to reduce delayed or
unnecessary treatment. While language serves as an indispensable source of information …