Promising Use of Big Data to Increase the Efficiency and Comprehensiveness of Stroke Outcomes Research

Author:

Ung David1,Kim Joosup12,Thrift Amanda G.1,Cadilhac Dominique A.12,Andrew Nadine E.13,Sundararajan Vijaya45,Kapral Moira K.6,Reeves Mathew7,Kilkenny Monique F.12

Affiliation:

1. From the Stroke and Ageing Research, Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, Australia (D.U., J.K., A.G.T., D.A.C., N.E.A., M.F.K.)

2. Stroke Division, The Florey Institute of Neuroscience and Mental Health, Heidelberg, VIC, Australia (J.K., D.A.C., M.F.K.)

3. Peninsula Clinical School, Central Clinical School, Monash University, Frankston, VIC, Australia (N.E.A.)

4. La Trobe University, Melbourne, VIC, Australia (V.S.)

5. Department of Public Health, School of Psychology and Public Health, College of Science Health and Engineering, La Trobe University, Bundoora, VIC, Australia (V.S.)

6. Division of General Internal Medicine, Department of Medicine, University of Toronto, ON, Canada (M.K.K.)

7. Department of Epidemiology and Biostatistics, College of Human Medicine, Michigan State University, East Lansing, MI (M.R.).

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Advanced and Specialized Nursing,Cardiology and Cardiovascular Medicine,Neurology (clinical)

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