MOESM4 of An unsupervised learning approach to identify novel signatures of health and disease from multimodal data

Additional file 4. Multimodal correlation data.

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Identity

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PID https://www.doi.org/10.6084/m9.figshare.11574336.v1
PID https://www.doi.org/10.6084/m9.figshare.11574336
URL https://figshare.com/articles/MOESM4_of_An_unsupervised_learning_approach_to_identify_novel_signatures_of_health_and_disease_from_multimodal_data/11574336
URL http://dx.doi.org/10.6084/m9.figshare.11574336.v1
URL https://dx.doi.org/10.6084/m9.figshare.11574336
URL http://dx.doi.org/10.6084/m9.figshare.11574336
URL https://dx.doi.org/10.6084/m9.figshare.11574336.v1
Access Modality

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Access Right Open Access
Attribution

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Author Shomorony, Ilan
Author Cirulli, Elizabeth
Author Huang, Lei
Author Napier, Lori
Author Heister, Robyn
Author Hicks, Michael
Author Cohen, Isaac
Author Yu, Hung-Chun
Author Swisher, Christine
Author Schenker-Ahmed, Natalie
Author Li, Weizhong
Author Nelson, Karen
Author Brar, Pamila
Author Kahn, Andrew
Author Spector, Timothy
Author Caskey, C.
Author Venter, J.
Author Karow, David
Author Kirkness, Ewen
Author Shah, Naisha
Publishing

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Collected From Datacite; figshare
Hosted By figshare
Publication Date 2020-01-11
Publisher figshare
Additional Info
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Language UNKNOWN
Resource Type Dataset
keyword ACM.InformationSystems_INFORMATIONINTERFACESANDPRESENTATION_e.g.,HCI_
keyword FOS: Mathematics
keyword FOS: Biological sciences
keyword FOS: Computer and information sciences
system:type dataset
Management Info
Field Value
Source https://science-innovation-policy.openaire.eu/search/dataset?datasetId=dedup_wf_001::f21bd024a77978320ca6749c349214f9
Author jsonws_user
Version None
Last Updated 5 January 2021, 02:10 (CET)
Created 5 January 2021, 02:10 (CET)