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Big data and data repurposing - using existing data to answer new questions in vascular dementia research
Fergus N Doubal1, Myzoon Ali2, G David Batty3
1Stroke Association Garfield Weston Foundation Clinical Senior Lecturer, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK. Fergus.doubal@ed.ac.uk.
BMC Neurology
|April 18, 2017
Summary
Novel data synthesis methods offer promising avenues for advancing vascular dementia (VaD) research by enabling efficient hypothesis generation and testing. These approaches leverage existing data to accelerate understanding and treatment development for VaD.
Area of Science:
- Neuroscience
- Data Science
- Clinical Research
Background:
- Traditional clinical research has not yielded effective vascular dementia (VaD) treatments.
- Novel data collation and synthesis methods can accelerate hypothesis generation and testing for complex conditions like VaD.
Purpose of the Study:
- To present an overview of innovative uses for existing data to advance vascular dementia (VaD) research.
- To explore opportunities for data repurposing in VaD research through stakeholder consultation and literature review.
Main Methods:
- Overview of new data uses for VaD research.
- Consultation with stakeholders and literature review.
- Learning from expert discussions at the 9th International Congress on Vascular Dementia.
Main Results:
- Key areas identified: systematic review of existing studies, individual patient-level analyses of trials/cohorts, and linking electronic health records.
- Case studies illustrated the application of these data repurposing approaches.
Conclusions:
- Significant opportunities exist for the VaD research community to optimize the use of existing data.
- Increasing data volumes and novel analytical methods present exciting prospects for VaD research progress.
- Maintaining rigor and critical analysis is crucial to overcome limitations and biases associated with large datasets.