Canadian Neurological Sciences Federation 2022 Congress, CNSF
Canadian Journal of Neurological Sciences
; 49, 2022.
Article
in English
| EMBASE | ID: covidwho-2002963
ABSTRACT
The proceedings contain 174 papers. The topics discussed include deep learning prediction of response to disease modifying therapy in primary progressive multiple sclerosis;changes in ischemic stroke presentations and associated workflow during the first wave of the COVID-19 pandemic a population study;a novel recessive TNNT1 congenital core-rod myopathy in French Canadians;identification of predictors of response to Erenumab in episodic and chronic migraine in a cohort of patients a preliminary analysis;entropy on routine EEG an interictal marker of seizure frequency?;can quantitative susceptibility mapping help diagnose and predict recovery of concussion in children?;neuropathology of eight cases of the new Brunswick cluster of neurological syndrome of unknown cause (NSUC);does gender equality exist in the surgical management of degenerative lumbar disease?;cerebral venous sinus thrombosis in preterm infants;endovascular treatment of acute ischemic stroke in patients with pre-morbid disability a meta-analysis;and muscular MRI pattern recognition for muscular dystrophies the era of artificial intelligence beyond a systematic review.
erenumab; acute ischemic stroke; artificial intelligence; Canadian; cerebral sinus thrombosis; child; cohort analysis; concussion; conference review; coronavirus disease 2019; deep learning; disability; electroencephalogram; entropy; female; gender equity; human; male; meta analysis; multiple sclerosis; muscular dystrophy; nemaline myopathy; neurologic disease; neuropathology; New Brunswick; nuclear magnetic resonance imaging; pandemic; pattern recognition; population research; prediction; prematurity; quantitative analysis; seizure; systematic review; transformed migraine; workflow
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Collection:
Databases of international organizations
Database:
EMBASE
Language:
English
Journal:
Canadian Journal of Neurological Sciences
Year:
2022
Document Type:
Article
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