661 a 670 de 1.101 Resultados
3 jun 2021 -
Formal concept analysis for topic detection: a clustering quality experimental analysis
Texto plano - 4,8 KB -
MD5: a4c7c08bab5647aea051fd0737be1b0e
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Lastra-Díaz, Juan J.; Lara-Clares, Alicia; Garcia-Serrano, Ana M., 2020, "Reproducibility dataset for a benchmark of biomedical semantic measures libraries", https://doi.org/10.21950/OTDA4Z, e-cienciaDatos, V5
This dataset introduces a set of reproducibility resources with the aim of allowing the exact replication of the experiments introduced by our companion paper, which compare the performance of the three UMLS-based semantic similarity libraries reported in the literature as follow... |
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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Nuria Escribano Mediavilla; Virginia Belliard-Tiol; María Victoria Fuentes Fuentes; Bruno Baracco Cabañes; Dayana Da Silva Gonçales; Laura Ceballos, 2021, "Rubric for Evaluation of Endodontic Treatments Performed by Dental Students", https://doi.org/10.21950/DPNC8Q, e-cienciaDatos, V1
Rubric designed for the evaluation of portfolios of endodontic pre-clinical treatments performed by dental students |
Texto plano - 2,3 KB -
MD5: 26917a7e477f4bd6e5088074aec6aae4
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Adobe PDF - 75,3 KB -
MD5: b7a014fdb4b867634ece9d87ffa8b529
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