Please use this identifier to cite or link to this item:
http://ahro.austin.org.au/austinjspui/handle/1/22425| Title: | Promising Use of Big Data to Increase the Efficiency and Comprehensiveness of Stroke Outcomes Research. |
| 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 |
| Citation: | Stroke 2019; 50(5): 1302-1309 |
| URI: | http://ahro.austin.org.au/austinjspui/handle/1/22425 |
| DOI: | 10.1161/STROKEAHA.118.020372 |
| ORCID: | 0000-0001-8162-682X 0000-0002-3375-287X |
| PubMed URL: | 31009352 |
| Type: | Journal Article Review |
| Subjects: | big data cohort studies data collection data linkage mortality registries stroke |
| Appears in Collections: | Journal articles |
Files in This Item:
There are no files associated with this item.
Items in AHRO are protected by copyright, with all rights reserved, unless otherwise indicated.