Medical terminology-based computing system: a lightweight post-processing solution for out-of-vocabulary multi-word terms.

ABSTRACT: The linguistic rules of medical terminology assist in gaining acquaintance with rare/complex clinical and biomedical terms. The medical language follows a Greek and Latin-inspired nomenclature. This nomenclature aids the stakeholders in simplifying the medical terms and gaining semantic familiarity. However, natural language processing models misrepresent rare and complex biomedical words. In this study, we present MedTCS-a lightweight, post-processing module-to simplify hybridized or compound terms into regular words using medical nomenclature. MedTCS enabled the word-based embedding models to achieve 100% coverage and enabled the BiowordVec model to achieve high correlation scores (0.641 and 0.603 in UMNSRS similarity and relatedness datasets, respectively) that significantly surpass the

SUBMITTER: Saeed N 

PROVIDER: S-EPMC9411640 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature