Encuesta satisfacción e-cienciaDatos
e-cienciaDatos es el repositorio de datos de investigación de las universidades del Consorcio Madroño. Es miembro de Harvard Dataverse Network, aceptado por las principales editoriales científicas y cumple los requisitos del H2020.
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Gracias por su colaboración.
1 a 10 de 11 Resultados
Archivo Gzip - 574,8 KB -
MD5: 77aee55e76f1cf515b04740c746e524f
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Sintasis R - 63,4 KB -
MD5: 286b156419070aa804bc233a6bb8b3b0
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application/mac-compactpro - 4,0 GB -
MD5: 3c74a196b4775bc558986f597bfa9f73
In order to obtain a decrypt password for this, you should sign and obtain a license for the National Library of Medicine (NLM) of the United States to use the UMLS Metathesaurus databases, as well as SNOMED-CT and MeSH ontologies included in this Docker image. For this purpose,... |
application/mac-compactpro - 73,9 MB -
MD5: 36dc6139142c18e2b50c5bd8fa573e5f
In order to obtain a decrypt password for this, you should sign and obtain a license for the National Library of Medicine (NLM) of the United States to use the UMLS Metathesaurus databases, as well as SNOMED-CT and MeSH ontologies included in this Docker image. For this purpose,... |
Adobe PDF - 437,8 KB -
MD5: 352489b0a4478adbde75ca4790159e7b
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application/mac-compactpro - 66,0 GB -
MD5: cf5d23e515313d35a1a3d959e0140ed9
In order to obtain a decrypt password for this, you should sign and obtain a license for the National Library of Medicine (NLM) of the United States to use the UMLS Metathesaurus databases, as well as SNOMED-CT and MeSH ontologies included in this Docker image. For this purpose,... |
Archivo Gzip - 573,0 KB -
MD5: f21249e966162907d8c08edeb7f1851a
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Archivo Gzip - 573,5 KB -
MD5: 53086a1feda2458b97dfad161fc256f5
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18 dic. 2020 -
Reproducible experiments on the master thesis: An experimental survey of Named Entity Recognition methods in the biomedical domain
Texto plano - 6,1 KB -
MD5: 1dd80692aac37dccc56aa55ef2086581
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18 dic. 2020 -
Reproducible experiments on the master thesis: An experimental survey of Named Entity Recognition methods in the biomedical domain
Adobe PDF - 163,8 KB -
MD5: ceec87c68a5dc590ba4ad1dca2709bc6
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