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A parameter-efficient deep learning approach to predict conversion from mild cognitive impairment to Alzheimer's disease

Crossref DOI link: https://doi.org/10.1016/j.neuroimage.2019.01.031

Published Print: 2019-04

Update policy: https://doi.org/10.1016/elsevier_cm_policy

Authors

Spasov, Simeon

Passamonti, Luca

Duggento, Andrea

Liò, Pietro

Toschi, Nicola
Funding

Funding for this research was provided by:

Medical Research Council (MR/P01271X/1)

Engineering and Physical Sciences Research Council (EP/L015889/1)

National Institute on Aging

National Institutes of Health
License Information

Text and Data Mining valid from 2019-04-01

Text and Data Mining valid from 2019-04-01

Accepted Manuscript valid from 2020-01-23
More Information

This article is maintained by: Elsevier

Article Title: A parameter-efficient deep learning approach to predict conversion from mild cognitive impairment to Alzheimer's disease

Journal Title: NeuroImage

CrossRef DOI link to publisher maintained version: https://doi.org/10.1016/j.neuroimage.2019.01.031

Content Type: article

Copyright: © 2019 Elsevier Inc. All rights reserved.