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The pursuit of approaches to federate data to accelerate Alzheimer's disease and related dementia research: GAAIN, DPUK, and ADDI.
Toga, Arthur W; Phatak, Mukta; Pappas, Ioannis; Thompson, Simon; McHugh, Caitlin P; Clement, Matthew H S; Bauermeister, Sarah; Maruyama, Tetsuyuki; Gallacher, John.
Afiliación
  • Toga AW; Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States.
  • Phatak M; Alzheimer's Disease Data Initiative, Kirkland, WA, United States.
  • Pappas I; Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States.
  • Thompson S; Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, United Kingdom.
  • McHugh CP; Alzheimer's Disease Data Initiative, Kirkland, WA, United States.
  • Clement MHS; Alzheimer's Disease Data Initiative, Kirkland, WA, United States.
  • Bauermeister S; Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, United Kingdom.
  • Maruyama T; Alzheimer's Disease Data Initiative, Kirkland, WA, United States.
  • Gallacher J; Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, United Kingdom.
Front Neuroinform ; 17: 1175689, 2023.
Article en En | MEDLINE | ID: mdl-37304174
ABSTRACT
There is common consensus that data sharing accelerates science. Data sharing enhances the utility of data and promotes the creation and competition of scientific ideas. Within the Alzheimer's disease and related dementias (ADRD) community, data types and modalities are spread across many organizations, geographies, and governance structures. The ADRD community is not alone in facing these challenges, however, the problem is even more difficult because of the need to share complex biomarker data from centers around the world. Heavy-handed data sharing mandates have, to date, been met with limited success and often outright resistance. Interest in making data Findable, Accessible, Interoperable, and Reusable (FAIR) has often resulted in centralized platforms. However, when data governance and sovereignty structures do not allow the movement of data, other methods, such as federation, must be pursued. Implementation of fully federated data approaches are not without their challenges. The user experience may become more complicated, and federated analysis of unstructured data types remains challenging. Advancement in federated data sharing should be accompanied by improvement in federated learning methodologies so that federated data sharing becomes functionally equivalent to direct access to record level data. In this article, we discuss federated data sharing approaches implemented by three data platforms in the ADRD field Dementia's Platform UK (DPUK) in 2014, the Global Alzheimer's Association Interactive Network (GAAIN) in 2012, and the Alzheimer's Disease Data Initiative (ADDI) in 2020. We conclude by addressing open questions that the research community needs to solve together.
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Texto completo: 1 Base de datos: MEDLINE Idioma: En Revista: Front Neuroinform Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Base de datos: MEDLINE Idioma: En Revista: Front Neuroinform Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos