Results 41 to 50 of about 4,607 (172)
Abstract Objective Nonconvulsive epileptic activity is common after acute brain injury and contributes to neuronal injury and poor outcomes. Although intracranial electroencephalography (iEEG) improves detection compared with surface EEG (suEEG), it currently relies on focal recordings of epileptic dynamics.
Steven Smeijers +7 more
wiley +1 more source
Pediatric epilepsy surgery: Global survey of invasive explorations
Abstract Objective Invasive presurgical evaluation plays a key role in pediatric epilepsy surgery, particularly in magnetic resonance imaging (MRI)‐negative cases, by guiding resective, disconnective, or ablative procedures. This International League Against Epilepsy (ILAE) Pediatric Epilepsy Surgery Taskforce study provides an updated global overview ...
Georgia Ramantani +96 more
wiley +1 more source
Kyphosis – A risk factor for positioning brachial plexopathy during spinal surgeries
Objective: The aim of this study was to evaluate the differences in transcranial electric motor-evoked potentials – TceMEP on upper limbs and the incidences of postoperative brachial plexopathy between patients with kyphotic and scoliotic trunk shapes ...
Mirza Biscevic +6 more
doaj +1 more source
The Use of Intraoperative Neurophysiological Monitoring in Spine Surgery
Study Design: Narrative review. Objective: To summarize relevant studies regarding the utilization of intraoperative neurophysiological monitoring (IONM) techniques in spine surgery implemented in recent years. Methods: A literature search of the Medline
Anastasios Charalampidis MD +5 more
doaj +1 more source
BackgroundThe use of intraoperative neurophysiological monitoring, including direct nerve stimulation (especially the facial nerve), acoustic evoked potentials (AEP) and somatosensory evoked potentials (SSEP), is a helpful tool in the microsurgery of ...
Felix Arlt +6 more
doaj +1 more source
AI‐based localization of the epileptogenic zone using intracranial EEG
Abstract Artificial intelligence (AI) is rapidly transforming our lives. Machine learning (ML) enables computers to learn from data and make decisions without explicit instructions. Deep learning (DL), a subset of ML, uses multiple layers of neural networks to recognize complex patterns in large datasets through end‐to‐end learning.
Atsuro Daida +5 more
wiley +1 more source
Intraoperative neurophysiological monitoring team's communiqué with anesthesia professionals
Background and Aims: Intraoperative neurophysiological monitoring (IONM) is the standard of care during many spinal, vascular, and intracranial surgeries.
Anurag Tewari +6 more
doaj +1 more source
Research progress on the depth of anesthesia monitoring based on the electroencephalogram
Electroencephalogram (EEG) can noninvasive, continuous, and real‐time monitor the state of brain electrical activity, and the monitoring of EEG can reflect changes in the depth of anesthesia (DOA). The development of artificial intelligence can enable anesthesiologists to extract, analyze, and quantify DOA from complex EEG data.
Xiaolan He, Tingting Li, Xiao Wang
wiley +1 more source
Abstract Adaptive deep brain stimulation (aDBS) represents an important evolution in the treatment of Parkinson's disease (PD), building on conventional DBS (cDBS) by adjusting stimulation in response to real‐time physiological signals. By enabling dynamic targeting of disease‐related neural activity, aDBS offers the potential for more precise ...
Thomas Koeglsperger +5 more
wiley +1 more source
Abstract Background The posterior subthalamic area (PSA) is a familiarized target for Parkinson's disease (PD) in the lesioning era and has recently been reconsidered for deep brain stimulation (DBS). Objective The aim of this study was to compare the therapeutic efficacy of PSA versus subthalamic nucleus (STN) DBS in tremor‐dominant Parkinson's ...
Zhengyu Lin +7 more
wiley +1 more source

