Published on in Vol 7, No 4 (2019): Oct-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/14782, first published .
Efficient Reuse of Natural Language Processing Models for Phenotype-Mention Identification in Free-text Electronic Medical Records: A Phenotype Embedding Approach

Efficient Reuse of Natural Language Processing Models for Phenotype-Mention Identification in Free-text Electronic Medical Records: A Phenotype Embedding Approach

Efficient Reuse of Natural Language Processing Models for Phenotype-Mention Identification in Free-text Electronic Medical Records: A Phenotype Embedding Approach

Honghan Wu   1, 2, 3 , BEng, DPhil ;   Karen Hodgson   4 , DPhil ;   Sue Dyson   4 , MD ;   Katherine I Morley   4, 5, 6 , DPhil ;   Zina M Ibrahim   4, 7 , DPhil ;   Ehtesham Iqbal   4 , BEng ;   Robert Stewart   4, 5 , MD, DPhil ;   Richard JB Dobson   4, 7 , DPhil ;   Cathie Sudlow   1, 3 , MD, DPhil

1 Centre for Medical Informatics, Usher Institute, University of Edinburgh, Edinburgh, United Kingdom

2 School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, China

3 Health Data Research UK, University of Edinburgh, Edinburgh, United Kingdom

4 Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom

5 South London and Maudsley NHS Foundation Trust, London, United Kingdom

6 Centre for Epidemiology and Biostatistics, Melbourne School of Global and Population Health, The University of Melbourne, Melbourne, Australia

7 Health Data Research UK, University College London, London, United Kingdom

Corresponding Author:

  • Honghan Wu, BEng, DPhil
  • Centre for Medical Informatics
  • Usher Institute
  • University of Edinburgh
  • 9 Little France Road
  • Edinburgh, EH16 4UX
  • United Kingdom
  • Phone: 44 01316517882
  • Email: honghan.wu@ed.ac.uk