Epilepsy is a common and serious neurological disorder, with many different constituent
conditions characterized by their electro clinical, imaging, and genetic features. MRI has …

Abstract Machine learning is playing an increasingly important role in medical image
analysis, spawning new advances in the clinical application of neuroimaging. There have …

Drug‐resistant epilepsy (DRE) considerably affects patient health, cognition, and well‐
being, and disproportionally contributes to the overall burden of epilepsy. The most common …

Objective We evaluated whether deep learning applied to whole‐brain presurgical structural
connectomes could be used to predict postoperative seizure outcome more accurately than …

Epilepsy is a common neurological disorder associated with alterations in cortical and
subcortical brain networks. Despite a historical focus on gray matter regions involved in …

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 …

Objective The distributed white matter network underlying language leads to difficulties in
extracting clinically meaningful summaries of neural alterations leading to language …

OBJECTIVE Risk for memory decline is a common concern for individuals with temporal
lobe epilepsy (TLE) undergoing surgery. Global and local network abnormalities are well …

The traditional linear regression in applied linguistics (AL) suffers from the drawbacks
arising from the strict assumptions namely: linearity, and normality, etc. More advanced …

Neurons are interactive cells that connect via ions to develop electromagnetic fields in the
brain. This structure functions directly in the brain. Connectome is the data obtained from …