A5007948115- Acute Ischemic Stroke Management
- Cerebrovascular and Carotid Artery Diseases
- Epilepsy research and treatment
- EEG and Brain-Computer Interfaces
- Traumatic Brain Injury and Neurovascular Disturbances
- Intracranial Aneurysms: Treatment and Complications
- Vascular Malformations Diagnosis and Treatment
- Peripheral Neuropathies and Disorders
- Venous Thromboembolism Diagnosis and Management
- Cerebral Venous Sinus Thrombosis
- Intracerebral and Subarachnoid Hemorrhage Research
- Blind Source Separation Techniques
- Autoimmune Neurological Disorders and Treatments
- Infectious Encephalopathies and Encephalitis
- ECG Monitoring and Analysis
- Neurological and metabolic disorders
- Neuroscience and Neural Engineering
- Neonatal and fetal brain pathology
- Meningioma and schwannoma management
- Stroke Rehabilitation and Recovery
- Bacterial Infections and Vaccines
- Alcoholism and Thiamine Deficiency
- Atomic and Subatomic Physics Research
- Peripheral Nerve Disorders
- Neuroscience and Neuropharmacology Research
National University Health System
2013-2025
National University of Singapore
2014-2025
National University Hospital
2013-2025
University Health System
2018
National Neuroscience Institute
2016
Raffles Institution
2016
Neurosciences Institute
2016
Heidelberg University
2014
National Brain Centre
2014
National University of Health Sciences
2013-2014
<h3>BACKGROUND AND PURPOSE:</h3> Intracranial collaterals influence the prognosis of patients treated with intravenous tissue plasminogen activator in acute anterior circulation ischemic stroke. We compared methods scoring on pre-tPA brain CT angiography for predicting functional outcomes <h3>MATERIALS METHODS:</h3> Two hundred consecutive stroke IV-tPA during 2010–2012 were included. independent neuroradiologists evaluated intracranial by using Miteff system, Maas modified Tan scale, and...
Visual evaluation of electroencephalogram (EEG) for Interictal Epileptiform Discharges (IEDs) as distinctive biomarkers epilepsy has various limitations, including time-consuming reviews, steep learning curves, interobserver variability, and the need specialized experts. The development an automated IED detector is necessary to provide a faster reliable diagnosis epilepsy. In this paper, we propose based on Convolutional Neural Networks (CNNs). We have evaluated proposed sizable database 554...
Recanalization of occluded intracranial arteries remains the aim intravenous (IV) tissue plasminogen activator (tPA) therapy in acute ischemic stroke (AIS).To examine timing and impact recanalization on functional outcomes AIS.A longitudinal cohort consecutive IV tPA–treated patients with AIS from January 2007 through December 2010. Data were collected for demography, risk factors, subtypes, blood pressure, National Institutes Health Stroke Scale scores. Early (ER) was identified by...
In acute ischemic stroke, large early infarct size estimated by the Alberta Stroke Program Early CT Score (ASPECTS) is associated with poorer outcomes and a relative contraindication for recanalization therapies. The state of intracranial collateral circulation influences functional outcome may be variable to consider before thrombolysis. We evaluated prognostic effect in patients thrombolyzed stroke who have sizes as indicated low ASPECTS.Patients anterior received computed tomographic...
The diagnosis of epilepsy often relies on a reading routine scalp electroencephalograms (EEGs). Since seizures are highly unlikely to be detected in EEG, the primary depends heavily visual evaluation Interictal Epileptiform Discharges (IEDs). This process is tedious, expert-centered, and delays treatment plan. Consequently, development an automated, fast, reliable epileptic EEG diagnostic system essential. In this study, we propose classify as or normal based multiple modalities extracted...
Epilepsy diagnosis based on Interictal Epileptiform Discharges (IEDs) in scalp electroencephalograms (EEGs) is laborious and often subjective. Therefore, it necessary to build an effective IED detector automatic method classify IED-free versus EEGs. In this study, we evaluate features that may provide reliable detection EEG classification. Specifically, investigate the convolutional neural network (ConvNet) with different input (temporal, spectral, wavelet features). We explore ConvNet...
Cytokine profiling before immunotherapy is increasingly prevalent in febrile infection-related epilepsy syndrome (FIRES). In this case, an 18-year-old man presented with first-onset seizure after a nonspecific illness. He developed super-refractory status epilepticus requiring multiple antiseizure medications and general anesthetic infusions. was treated pulsed methylprednisolone plasma exchange started on ketogenic diet. Contrast-enhanced MRI brain revealed postictal changes. EEG findings...
In simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), increased neuronal activity from epileptiform spikes commonly elicits positive blood oxygenation level-dependent (BOLD) responses. Negative responses are also occasionally seen have not been explained. Recent studies describe BOLD signal changes before focal EEG spikes. We aimed to systematically study if the undershoot of a preceding response might explain negative in focus.Eighty-two patients...
We compared intracranial collaterals on pretreatment and day 2 brain CT angiograms (CTA) to assess their evolution relationship with functional outcomes in acute ischemic stroke (AIS) patients treated IV tissue plasminogen activator (tPA).Consecutive AIS who underwent CTA received tPA during 2010-2013 were included. Collaterals evaluated by independent neuroradiologists using 3 predefined criteria: the Miteff system, Maas 20-point collateral scale Alberta Stroke Program Early Score...
Epilepsy diagnosis through visual examination of interictal epileptiform discharges (IEDs) in scalp electroencephalogram (EEG) signals is a challenging problem. Deep learning methods can be an automated way to perform this task. In work, we present new approach based on convolutional neural network (CNN) detect IEDs from EEGs automatically. The input CNN combination raw EEG and frequency sub-bands, namely delta, theta, alpha and, beta arranged as vector for one-dimensional (1D) or matrix...
Clinical diagnosis of epilepsy relies partially on identifying interictal epileptiform discharges (IEDs) in scalp electroencephalograms (EEGs). This process is expert-biased, tedious, and can delay the procedure. Beyond automatically detecting IEDs, there are far fewer studies automated methods to differentiate epileptic EEGs (potentially without IEDs) from normal EEGs. In addition, based a single EEG tends be low. Consequently, strong need for systems interpretation. Traditionally, heavily...
Pathological slowing in the electroencephalogram (EEG) is widely investigated for diagnosis of neurological disorders. Currently, gold standard detection visual inspection EEG by experts, which time-consuming and subjective. To address those issues, we propose three automated approaches to detect EEG: Threshold-based Detecting System (TDS), Shallow Learning-based (SLDS), Deep (DLDS). These systems are evaluated on channel-, segment- EEG-level. The TDS, SLDS, DLDS performs prediction via...
Polymyxin-induced neuromuscular blockade is a rare but potentially fatal condition, with majority of cases that were reported between 1962 and 1973. We describe patient who developed hypercapnic respiratory failure after initiation polymyxin for multi-drug resistant Escherichia Coli bacteremia, due to polymyxin-induced dysfunction. After cessation polymyxin, he regained full strength, had complete resolution ptosis, was successfully extubated. In light the renewed use in this era...