Publications by authors named "Sulaiman I Abuhaiba"
Article Synopsis
- Many machine learning methods for predicting seizures from electroencephalograms lack transparency, leading to decreased trust from clinicians.
- This study reviews the effectiveness of three different machine learning approaches (logistic regression, support vector machines, convolutional neural networks) in providing explainable predictions to help clinicians understand model decisions.
- The findings suggest that while model transparency is important, it’s not the most critical factor; instead, enhancing understanding comes from developing systems that address signal dynamics and improve communication between data scientists and clinicians.
Objectives: We aimed to investigate the antiepileptic effects of cathodal transcranial direct current stimulation (c-tDCS) and mechanisms of action based on its effects on the neurotransmitters responsible for the abnormal synchrony patterns seen in pharmacoresistant epilepsy. This is the first study to test the impact of neurostimulation on epileptiform interictal discharges (IEDs) and to measure brain metabolites in the epileptogenic zone (EZ) and control regions simultaneously in patients with pharmacoresistant epilepsy.
Methods: This is a hypothesis-driven pilot prospective single-blinded repeated measure design study in patients diagnosed with pharmacoresistant epilepsy of temporal lobe onset.
High-frequency activity (HFA) is believed to subserve a functional role in cognition, but these patterns are often not accessible to scalp EEG recordings. Intracranial studies provide a unique opportunity to link the all-encompassing range of high-frequency patterns with holistic perception. We tested whether the functional topography of HFAs (up to 250Hz) is related to perceptual decision-making.
View Article and Find Full Text PDFVisual impairment is one of the most feared complications of Type 2 Diabetes Mellitus. Here, we aimed to investigate the role of occipital cortex γ-aminobutyric acid (GABA) as a predictor of visual performance in type 2 diabetes. 18 type 2 diabetes patients were included in a longitudinal prospective one-year study, as well as 22 healthy age-matched controls.
View Article and Find Full Text PDF