Evaluating Medical Lexical Simplification: Rule-Based vs. BERT

Stud Health Technol Inform. 2021 May 27;281:1023-1024. doi: 10.3233/SHTI210337.

Abstract

Lexical simplification (LS) can decrease the communication gap between medical experts and laypeople by replacing medical terms with layperson counterparts. In this paper, we present: 1) a rule-based approach to LS using a consumer health vocabulary, and 2) an unsupervised approach using BERT to generate word candidates. Human evaluation shows that the unsupervised model performed better for simplicity and grammaticality, while the rule-based method was better at meaning preservation.

Keywords: Health Vocabulary; Lexical Simplification; Machine Learning.

MeSH terms

  • Communication*
  • Humans
  • Research Design
  • Vocabulary
  • Vocabulary, Controlled*