<p>Machine learning models for the clinical development of gene and cell therapies</p>

Albert A. Taylor; Samad Jahandideh; Danielle Beaulieu; Mike Keymer; David L. Ennist

doi:10.7490/f1000research.1114991.1

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Taylor AA, Jahandideh S, Beaulieu D et al. Machine learning models for the clinical development of gene and cell therapies [version 1; not peer reviewed]. F1000Research 2017, 6:1866 (poster) (https://doi.org/10.7490/f1000research.1114991.1)

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Machine learning models for the clinical development of gene and cell therapies

Albert A. Taylor, Samad Jahandideh, Danielle Beaulieu, Mike Keymer, David L. Ennist¹

Published 20 Oct 2017 (https://doi.org/10.7490/f1000research.1114991.1)

Author Affiliations

¹ Origent Data Sciences, Inc., USA

Copyright © 2017 Taylor AA 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 20 Oct 2017

Machine learning models for the clinical development of gene and cell therapies
[version 1; not peer reviewed]

Albert A. Taylor, Samad Jahandideh, Danielle Beaulieu, Mike Keymer, David L. Ennist¹

Author Affiliations

¹ Origent Data Sciences, Inc., USA

Presented at

20th American Society of Gene and Cell Therapy (ASGCT) Annual Meeting 2017

Abstract

Competing Interests

I am an employee and stock owner of Origent Data Sciences, Inc.

Keywords

Disease progression, clinical trial, virtual control, historic control, gene therapy, cell therapy, placebo arm

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