<p>Increasing study power using a machine learning approach</p>

Danielle Beaulieu; Albert A. Taylor; Andrew  Conklin; Jonavelle  Cuerdo; Mike Keymer; David L. Ennist

doi:10.7490/f1000research.1116287.1

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Beaulieu D, Taylor AA, Conklin A et al. Increasing study power using a machine learning approach [version 1; not peer reviewed]. F1000Research 2018, 7:1785 (poster) (https://doi.org/10.7490/f1000research.1116287.1)

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Increasing study power using a machine learning approach

Danielle Beaulieu, Albert A. Taylor, Andrew Conklin, Jonavelle Cuerdo, Mike Keymer, David L. Ennist¹

Published 12 Nov 2018 (https://doi.org/10.7490/f1000research.1116287.1)

Author Affiliations

¹ Origent Data Sciences, Inc., USA

Copyright © 2018 Beaulieu D 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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CITE

Published 12 Nov 2018

Increasing study power using a machine learning approach
[version 1; not peer reviewed]

Danielle Beaulieu, Albert A. Taylor, Andrew Conklin, Jonavelle Cuerdo, Mike Keymer, David L. Ennist¹

Author Affiliations

¹ Origent Data Sciences, Inc., USA

Presented at

Joint Statistical Meeting of the American Statistical Association 2018

Abstract

Competing Interests

No competing interests were disclosed

Keywords

Study power, machine learning, ALS

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