Natural language processing: Use in EBM and a guide for appraisal

Mouaz Alsawas, Fares Alahdab, Noor Asi, Ding Cheng Li, Zhen Wang, M. Hassan Murad

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Studies using natural language processing (NLP) techniques are increasingly being published. Evidence-based medicine (EBM) users need to learn the basics of NLP to be able to appraise these types of studies. We propose a set of criteria to evaluate the quality of studies that have used NLP, focusing on the methods of sample selection, coding, the gold standard, algorithm training, algorithm testing and measures of accuracy (such as recall and precision). NLP has proven critical for conducting biomedical research and has the potential to improve healthcare practice and facilitate EBM. Stakeholders (healthcare providers and policymakers) interested in using evidence derived from studies that used NLP need to know the basics of NLP and need to be able to appraise this type of study.

Original languageEnglish (US)
Pages (from-to)136-138
Number of pages3
JournalEvidence-Based Medicine
Volume21
Issue number4
DOIs
StatePublished - Aug 2016

Keywords

  • EPIDEMIOLOGY
  • GENERAL MEDICINE (see Internal Medicine)
  • QUALITATIVE RESEARCH

ASJC Scopus subject areas

  • Medicine(all)

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