Your browser doesn't support javascript.
loading
Efficient Reuse of Natural Language Processing Models for Phenotype-Mention Identification in Free-text Electronic Medical Records: A Phenotype Embedding Approach.
Wu, Honghan; Hodgson, Karen; Dyson, Sue; Morley, Katherine I; Ibrahim, Zina M; Iqbal, Ehtesham; Stewart, Robert; Dobson, Richard Jb; Sudlow, Cathie.
Afiliação
  • Wu H; Centre for Medical Informatics, Usher Institute, University of Edinburgh, Edinburgh, United Kingdom.
  • Hodgson K; School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, China.
  • Dyson S; Health Data Research UK, University of Edinburgh, Edinburgh, United Kingdom.
  • Morley KI; Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.
  • Ibrahim ZM; Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.
  • Iqbal E; Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.
  • Stewart R; South London and Maudsley NHS Foundation Trust, London, United Kingdom.
  • Dobson RJ; Centre for Epidemiology and Biostatistics, Melbourne School of Global and Population Health, The University of Melbourne, Melbourne, Australia.
  • Sudlow C; Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.
JMIR Med Inform ; 7(4): e14782, 2019 Dec 17.
Article em En | MEDLINE | ID: mdl-31845899

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Revista: JMIR Med Inform Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Reino Unido

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Revista: JMIR Med Inform Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Reino Unido