<p>Simplified Form of Recurrent Neural Networks for Predicting Alzheimer Disease Progression</p>

SAYANTAN KUMAR; Aditi  Gupta; Inez Oh; Suzanne  Schindler; Albert Lai; Philip Payne

doi:10.7490/f1000research.1118399.1

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KUMAR S, Gupta A, Oh I et al. Simplified Form of Recurrent Neural Networks for Predicting Alzheimer Disease Progression [version 1; not peer reviewed]. F1000Research 2020, 9:1397 (poster) (https://doi.org/10.7490/f1000research.1118399.1)

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Simplified Form of Recurrent Neural Networks for Predicting Alzheimer Disease Progression

SAYANTAN KUMAR¹, Aditi Gupta, Inez Oh, Suzanne Schindler, Albert Lai, Philip Payne

Published 03 Dec 2020 (https://doi.org/10.7490/f1000research.1118399.1)

Author Affiliations

¹ Institute for Informatics at Washington University in St. Louis, School of Medicine, USA

Copyright © 2020 KUMAR S et al. This is an open access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Published 03 Dec 2020

Simplified Form of Recurrent Neural Networks for Predicting Alzheimer Disease Progression
[version 1; not peer reviewed]

SAYANTAN KUMAR¹, Aditi Gupta, Inez Oh, Suzanne Schindler, Albert Lai, Philip Payne

Author Affiliations

¹ Institute for Informatics at Washington University in St. Louis, School of Medicine, USA

Abstract

Competing Interests

No competing interests were disclosed

Keywords

Disease progression modeling, Recurrent neural networks, Artificial Intelligence in Precision Medicine

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