Downloads provided by UsageCountsEfficient and Explainable Risk Assessments for Imminent Dementia in an Aging Cohort Study
Copyright policy )NSF| III: Large: Collaborative Research: Analysis Engineering for Robust End-to-End Data Science ,
NSF| Collaborative Research: ABI Innovation: Interpretable Machine Learning to Identify Molecular Markers for Complex Phenotypes ,
NIH| Interpretable Machine Learning to Identify Alzheimer's Disease Therapeutic Targets ,
NSF| CHS: Small: Support for Self-Tracking and Patient-Provider Collaboration Using Data for Multiple and Evolving Goals in People with Migraine
Nicasia Beebe-Wang; Alex Okeson; Tim Althoff; Su-In Lee;
Efficient and Explainable Risk Assessments for Imminent Dementia in an Aging Cohort Study
This is the accepted manuscript version of the work published in its final form as Beebe-Wang, Nicasia; Okeson, Alex; Althoff, Tim; Lee, Su-In. IEEE Journal of Biomedical and Health Informatics 25(7). doi.org/10.1109/JBHI.2021.3059563 Deposited by shareyourpaper.org and openaccessbutton.org. We've taken reasonable steps to ensure this content doesn't violate copyright. However, if you think it does you can request a takedown by emailing help@openaccessbutton.org.
- University of Mary United States
- Washington State University United States
- University of Washington United States
Cohort Studies, Aging, Humans, Dementia, Neuropsychological Tests, Risk Assessment, Aged
Cohort Studies, Aging, Humans, Dementia, Neuropsychological Tests, Risk Assessment, Aged
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These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
Citations provided by BIP!popularityPopularity provided by BIP!
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
Influence provided by BIP!impulseImpulse provided by BIP!
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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NSF| III: Large: Collaborative Research: Analysis Engineering for Robust End-to-End Data Science, NSF| Collaborative Research: ABI Innovation: Interpretable Machine Learning to Identify Molecular Markers for Complex Phenotypes, NIH| Interpretable Machine Learning to Identify Alzheimer's Disease Therapeutic Targets, NSF| CHS: Small: Support for Self-Tracking and Patient-Provider Collaboration Using Data for Multiple and Evolving Goals in People with Migraine
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