Clinical Natural Language Processing in languages other than English: opportunities and challenges.
Résumé
Background:
Natural language processing applied to clinical text or aimed at a clinical outcome has been thriving in
recent years. This paper offers the first broad overview of clinical Natural Language Processing (NLP) for languages
other than English. Recent studies are summarized to offer insights and outline opportunities in this area.
Main Body:
We envision three groups of intended readers: (1) NLP researchers leveraging experience gained in other
languages, (2) NLP researchers faced with establishing clinical text processing in a language other than English, and
(3) clinical informatics researchers and practitioners looking for resources in their languages in order to apply NLP
techniques and tools to clinical practice and/or investigation. We review work in clinical NLP in languages other than
English. We classify these studies into three groups: (i) studies describing the development of new NLP systems or
components de novo, (ii) studies describing the adaptation of NLP architectures developed for English to another
language, and (iii) studies focusing on a particular clinical application.
Conclusion:
We show the advantages and drawbacks of each method, and highlight the appropriate application
context. Finally, we identify major challenges and opportunities that will affect the impact of NLP on clinical practice
and public health studies in a context that encompasses English as well as other languages.