Collections
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| The National Center for Data to Health |
Clusters of CTS Open Access (recommended)
In a preliminary assessment of the CTS literature, natural language processing techniques were used to create a term co-occurrence network based on publications citing CTSA U54 awards through 2016. Relevant and non-relevant terms were distinguished algorithmically to yield a list of over 2K most-frequently occurring terms.
Descriptions
- Resource type(s)
- Image
- Keyword
- Scientometrics
CTSA
- Rights
- Attribution-ShareAlike 3.0 United States
- Creator
-
Holmes, Kristi
Mohammadi, Ehsan
Gutzman, Karen E
Shaw, Pamela L
- Publisher
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DigitalHub. Galter Health Sciences Library
- Date Created
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2017-04-08
- Language
- English
- Subject: MESH
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Translational Research, Biomedical
Bibliometrics
- Grants and funding
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UL1TR001422
- DOI
-
10.18131/G3VG8F
- ARK
-
ark:/c8131/g3vg8f
File Details
- File Properties
-
Mime type: image/png
File size: 1435.9 kB