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Variable interactions in risk factors for dementia

O'Donoghue, Jim and Roantree, Mark and McCarren, Andrew (2016) Variable interactions in risk factors for dementia. In: IEEE Tenth International Conference on Research Challenges in Information Science, 1 -3 Jun 2016, Grenoble. France.

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Current estimates predict 1 in 3 people born today will develop dementia, suggesting a major impact on future population health. As such, research needs to connect specialist clinicians, data scientists and the general public. The In-MINDD project seeks to address this through the provision of a Profiler, a socio-technical information system connecting all three groups. The public interact, providing raw data; data scientists develop and refine prediction algorithms; and clinicians use in-built services to inform decisions. Common across these groups are Risk Factors, used for dementia-free survival prediction. Risk interactions could greatly inform prediction but determining these interactions is a problem underpinned by massive numbers of possible combinations. Our research employs a machine learning approach to automatically select best performing hyperparameters for prediction and learns variable interactions in a non-linear survival-analysis paradigm. Demonstrating effectiveness, we evaluate this approach using longitudinal data with a relatively small sample size.

Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Uncontrolled Keywords:Neural networks; Dementia; Risk factor interactions; Survival analysis
Subjects:Computer Science > Machine learning
Computer Science > Artificial intelligence
Medical Sciences > Health
DCU Faculties and Centres:Research Initiatives and Centres > INSIGHT Centre for Data Analytics
DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Published in:10th {IEEE} International Conference on Research Challenges in Information Science. . IEEE.
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Science Foundation Ireland, European Framework Programme 7
ID Code:21189
Deposited On:01 Jul 2016 09:19 by Jim O'Donoghue. Last Modified 09 Oct 2017 10:28

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