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Title: Promising Use of Big Data to Increase the Efficiency and Comprehensiveness of Stroke Outcomes Research.
Austin Authors: Ung, David;Kim, Joosup;Thrift, Amanda G;Cadilhac, Dominique A;Andrew, Nadine E;Sundararajan, Vijaya;Kapral, Moira K;Reeves, Mathew;Kilkenny, Monique F
Affiliation: Stroke and Ageing Research, Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
Peninsula Clinical School, Central Clinical School, Monash University, Frankston, Victoria, Australia
Stroke Division, The Florey Institute of Neuroscience and Mental Health, Heidelberg, Victoria, Australia
La Trobe University, Melbourne, Victoria, Australia
Department of Public Health, School of Psychology and Public Health, College of Science Health and Engineering, La Trobe University, Bundoora, Victoria, Australia
Division of General Internal Medicine, Department of Medicine, University of Toronto, ON, Canada
Department of Epidemiology and Biostatistics, College of Human Medicine, Michigan State University, East Lansing, MI
Issue Date: May-2019
Publication information: Stroke 2019; 50(5): 1302-1309
DOI: 10.1161/STROKEAHA.118.020372
ORCID: 0000-0001-8162-682X
Journal: Stroke
PubMed URL: 31009352
Type: Journal Article
Subjects: big data
cohort studies
data collection
data linkage
Appears in Collections:Journal articles

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