Integrative approaches to improve the informativeness of deep learning models for human complex diseases

Kushal K. Dey; Samuel S. Kim; Steven Gazal; Joseph Nasser; Jesse M. Engreitz; Alkes L. Price

doi:10.1101/2020.09.08.288563

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Integrative approaches to improve the informativeness of deep learning models for human complex diseases

View ORCID ProfileKushal K. Dey, Samuel S. Kim, Steven Gazal, Joseph Nasser, Jesse M. Engreitz, Alkes L. Price

doi: https://doi.org/10.1101/2020.09.08.288563

Kushal K. Dey

1Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA

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ORCID record for Kushal K. Dey
For correspondence: kshldey@gmail.com

Samuel S. Kim

1Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA

2Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA

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Steven Gazal

1Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA

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Joseph Nasser

3Broad Institute of MIT and Harvard, Cambridge, MA, USA

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Jesse M. Engreitz

3Broad Institute of MIT and Harvard, Cambridge, MA, USA

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Alkes L. Price

1Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA

3Broad Institute of MIT and Harvard, Cambridge, MA, USA

4Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA

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https://github.com/kkdey/Imperio
https://alkesgroup.broadinstitute.org/LDSCORE/DeepLearning/Dey_DeepBoost_Imperio/

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Posted August 13, 2021.

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Integrative approaches to improve the informativeness of deep learning models for human complex diseases

Kushal K. Dey, Samuel S. Kim, Steven Gazal, Joseph Nasser, Jesse M. Engreitz, Alkes L. Price

bioRxiv 2020.09.08.288563; doi: https://doi.org/10.1101/2020.09.08.288563

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Integrative approaches to improve the informativeness of deep learning models for human complex diseases

Kushal K. Dey, Samuel S. Kim, Steven Gazal, Joseph Nasser, Jesse M. Engreitz, Alkes L. Price

bioRxiv 2020.09.08.288563; doi: https://doi.org/10.1101/2020.09.08.288563

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