"Vocabulary, Controlled" is a descriptor in the National Library of Medicine's controlled vocabulary thesaurus,
MeSH (Medical Subject Headings). Descriptors are arranged in a hierarchical structure,
which enables searching at various levels of specificity.
A specified list of terms with a fixed and unalterable meaning, and from which a selection is made when CATALOGING; ABSTRACTING AND INDEXING; or searching BOOKS; JOURNALS AS TOPIC; and other documents. The control is intended to avoid the scattering of related subjects under different headings (SUBJECT HEADINGS). The list may be altered or extended only by the publisher or issuing agency. (From Harrod's Librarians' Glossary, 7th ed, p163)
| Descriptor ID |
D018875
|
| MeSH Number(s) |
L01.453.245.945
|
| Concept/Terms |
Vocabulary, Controlled- Vocabulary, Controlled
- Controlled Vocabulary
- Controlled Vocabularies
- Vocabularies, Controlled
Controlled Thesaurus- Controlled Thesaurus
- Controlled Thesauri
- Thesauri, Controlled
- Thesaurus, Controlled
|
Below are MeSH descriptors whose meaning is more general than "Vocabulary, Controlled".
Below are MeSH descriptors whose meaning is more specific than "Vocabulary, Controlled".
This graph shows the total number of publications written about "Vocabulary, Controlled" by people in this website by year, and whether "Vocabulary, Controlled" was a major or minor topic of these publications.
To see the data from this visualization as text,
click here.
| Year | Major Topic | Minor Topic | Total |
|---|
| 2014 | 0 | 1 | 1 |
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Below are the most recent publications written about "Vocabulary, Controlled" by people in Profiles.
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Using natural language processing to identify problem usage of prescription opioids. Int J Med Inform. 2015 Dec; 84(12):1057-64.
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Negation's not solved: generalizability versus optimizability in clinical natural language processing. PLoS One. 2014; 9(11):e112774.
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PEDSnet: a National Pediatric Learning Health System. J Am Med Inform Assoc. 2014 Jul-Aug; 21(4):602-6.
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Normalization and standardization of electronic health records for high-throughput phenotyping: the SHARPn consortium. J Am Med Inform Assoc. 2013 Dec; 20(e2):e341-8.
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Informatics grand challenges in multi-institutional comparative effectiveness research. J Comp Eff Res. 2012 Sep; 1(5):373-6.
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Coding free text radiology reports using the Cancer Text Information Extraction System (caTIES). AMIA Annu Symp Proc. 2007 Oct 11; 889.
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MediClass: A system for detecting and classifying encounter-based clinical events in any electronic medical record. J Am Med Inform Assoc. 2005 Sep-Oct; 12(5):517-29.