Abstract In the recent 5 years (2014–2018), there has been growing interest in the use of
machine learning (ML) techniques to explore image diagnosis and prognosis of therapeutic …

Epilepsy is a common neurological disorder characterized by recurrent and disabling
seizures. An increasing number of clinical and experimental applications of machine …

Network control theory is increasingly used to profile the brain's energy landscape via
simulations of neural dynamics. This approach estimates the control energy required to …

Mesial temporal lobe epilepsy with hippocampal sclerosis (mTLE-HS) is the most common
type of focal epilepsy. The present study aimed to explore the expression and functions of …

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 …

In recent years, the field of neuroimaging has undergone dramatic development.
Specifically, of importance for clinicians and researchers managing patients with epilepsies …

Positron emission tomography (PET) and single photon emission computed tomography
(SPECT) can be used to assist localization of seizure foci in patients with drug-resistant …

Given improvements in computing power, artificial intelligence (AI) with deep learning has
emerged as the state-of-the art method for the analysis of medical imaging data and will …

Background Epilepsy is one of the most common neurological disorders. Approximately, one-
third of patients with epilepsy have seizures refractory to antiepileptic drugs and further …

It has been a clinically important, long-standing challenge to accurately localize
epileptogenic focus in drug-resistant focal epilepsy because more intensive intervention to …