Faculty, Staff and Student Publications
Publication Date
1-18-2024
Journal
Journal of the American Medical Informatics Association
DOI
10.1093/jamia/ocad216
PMID
37952122
PMCID
PMC10797266
PubMedCentral® Posted Date
11-10-2023
PubMedCentral® Full Text Version
Post-print
Abstract
Objective: To construct an exhaustive Complementary and Integrative Health (CIH) Lexicon (CIHLex) to help better represent the often underrepresented physical and psychological CIH approaches in standard terminologies, and to also apply state-of-the-art natural language processing (NLP) techniques to help recognize them in the biomedical literature.
Materials and methods: We constructed the CIHLex by integrating various resources, compiling and integrating data from biomedical literature and relevant sources of knowledge. The Lexicon encompasses 724 unique concepts with 885 corresponding unique terms. We matched these concepts to the Unified Medical Language System (UMLS), and we developed and utilized BERT models comparing their efficiency in CIH named entity recognition to well-established models including MetaMap and CLAMP, as well as the large language model GPT3.5-turbo.
Results: Of the 724 unique concepts in CIHLex, 27.2% could be matched to at least one term in the UMLS. About 74.9% of the mapped UMLS Concept Unique Identifiers were categorized as "Therapeutic or Preventive Procedure." Among the models applied to CIH named entity recognition, BLUEBERT delivered the highest macro-average F1-score of 0.91, surpassing other models.
Conclusion: Our CIHLex significantly augments representation of CIH approaches in biomedical literature. Demonstrating the utility of advanced NLP models, BERT notably excelled in CIH entity recognition. These results highlight promising strategies for enhancing standardization and recognition of CIH terminology in biomedical contexts.
Keywords
Algorithms, Unified Medical Language System, Natural Language Processing, Language, Complementary and Integrative Health, terminology, Unified Medical Language System, named entity recognition
Published Open-Access
yes
Recommended Citation
Zhou, Huixue; Austin, Robin; Lu, Sheng-Chieh; et al., "Complementary and Integrative Health Information in the Literature: Its Lexicon and Named Entity Recognition" (2024). Faculty, Staff and Student Publications. 5209.
https://digitalcommons.library.tmc.edu/uthgsbs_docs/5209
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