Systematized Nomenclature of Medicine-Clinical Terms
How to cite this record: FAIRsharing.org: SNOMEDCT; Systematized Nomenclature of Medicine-Clinical Terms; DOI: https://doi.org/10.25504/FAIRsharing.d88s6e; Last edited: Feb. 22, 2018, 2:16 p.m.; Last accessed: Apr 20 2018 7:45 a.m.
Developed in Australia , Belgium , Brunei , Canada , Chile , Czech Republic , Denmark , Estonia , Hong Kong , Iceland , India , Israel , Lithuania , Malaysia , Malta , Netherlands , New Zealand , Norway , Poland , Portugal , Republic of Ireland , Singapore , Slovakia , Slovenia , Spain , Sweden , Switzerland , United Kingdom , United States , Uruguay
Created in 2005
Scope and data types
|online documentation||http://www.ihtsdo.org/snomed-ct/what-is- ...|
|SNOMED CT Browser||https://confluence.ihtsdotools.org/display/TOOLS/SNOMED+CT+Browser||2.0|
|SNOMED CT Component Identifier Service||https://confluence.ihtsdotools.org/display/TOOLS/SNOMED+CT+Component+I ...||1.0|
|SNOMED CT Mapping Tool||https://confluence.ihtsdotools.org/display/TOOLS/SNOMED+CT+Mapping+Too ...||1.0|
No XSD schemas defined
Conditions of UseApplies to: Data use
REST Web Services
|Identity Management Service||https://confluence.ihtsdotools.org/display/TOOLS/Identity+Management+S ...|
Standardized nursing language in the systematized nomenclature of medicine clinical terms: A cross-mapping validation method.
Lu DF,Eichmann D,Konicek D,Park HT,Ucharattana P,Delaney C
Comput Inform Nurs 2006
View in BioPortal.
No guidelines defined
Models and Formats
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Microenvironment Perturbagen LINCS Center image server
The MEP LINCS project contributes to the development of the NIH Library of Integrated Network-based Cellular Signatures (LINCS) program by developing a dataset and computational strategy to elucidate how microenvironment (ME) signals affect cell intrinsic intracellular transcriptional- and protein-defined molecular networks to generate experimentally observable cellular phenotypes measured by high-content imaging.
The Project Tycho® database aims are to advance the availability and use of public health data for science and policy. We do this by acquisition of new data, by building infrastructure for data standardization, integration, quality control, and data redistribution, by developing innovative analytics, and by advocacy. Project Tycho contains a complete digitization of the entire history of weekly National Notifiable Disease Surveillance System (NNDSS) reports for the United States (1888-2013) into a database in computable format (Level 3 data). We have standardized a major part of these data for online access (Level 2 data). A subset of the U.S. data was cleaned further and used for a study on the impact of vaccination programs in the United States that was recently published in the NEJM (Level 1 data).
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