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Exploring semantic deep learning for building reliable and reusable one health knowledge from PubMed systematic reviews and veterinary clinical notes.
Arguello-Casteleiro, Mercedes; Stevens, Robert; Des-Diz, Julio; Wroe, Chris; Fernandez-Prieto, Maria Jesus; Maroto, Nava; Maseda-Fernandez, Diego; Demetriou, George; Peters, Simon; Noble, Peter-John M; Jones, Phil H; Dukes-McEwan, Jo; Radford, Alan D; Keane, John; Nenadic, Goran.
Afiliación
  • Arguello-Casteleiro M; School of Computer Science, University of Manchester, Manchester, UK. m.arguello@manchester.ac.uk.
  • Stevens R; School of Computer Science, University of Manchester, Manchester, UK.
  • Des-Diz J; Hospital do Salnés, Villagarcía de Arousa, Pontevedra, Spain.
  • Wroe C; BMJ, Tavistock Square, London, UK.
  • Fernandez-Prieto MJ; Salford Languages, University of Salford, Salford, UK.
  • Maroto N; Departamento de Lingüística Aplicada a la Ciencia y a la Tecnología, Universidad Politécnica de Madrid, Madrid, Spain.
  • Maseda-Fernandez D; Midcheshire Hospital Foundation Trust, NHS England, Crewe, UK.
  • Demetriou G; School of Medical Sciences, University of Manchester, Manchester, UK.
  • Peters S; School of Computer Science, University of Manchester, Manchester, UK.
  • Noble PM; School of Social Sciences, University of Manchester, Manchester, UK.
  • Jones PH; Small Animal Veterinary Surveillance Network, University of Liverpool, Liverpool, UK.
  • Dukes-McEwan J; Small Animal Veterinary Surveillance Network, University of Liverpool, Liverpool, UK.
  • Radford AD; Small Animal Teaching Hospital, University of Liverpool, Liverpool, UK.
  • Keane J; Small Animal Veterinary Surveillance Network, University of Liverpool, Liverpool, UK.
  • Nenadic G; School of Computer Science, University of Manchester, Manchester, UK.
J Biomed Semantics ; 10(Suppl 1): 22, 2019 11 12.
Article en En | MEDLINE | ID: mdl-31711540
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Semántica / Veterinarios / PubMed / Bases del Conocimiento / Salud Única / Aprendizaje Profundo / Revisiones Sistemáticas como Asunto Tipo de estudio: Guideline / Systematic_reviews Idioma: En Revista: J Biomed Semantics Año: 2019 Tipo del documento: Article País de afiliación: Reino Unido
Texto completo
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Semántica / Veterinarios / PubMed / Bases del Conocimiento / Salud Única / Aprendizaje Profundo / Revisiones Sistemáticas como Asunto Tipo de estudio: Guideline / Systematic_reviews Idioma: En Revista: J Biomed Semantics Año: 2019 Tipo del documento: Article País de afiliación: Reino Unido