Acupuncture indication knowledge bases: meridian entity recognition and classification based on ACUBERT.

ABSTRACT: In acupuncture diagnosis and treatment, non-quantitative clinical descriptions have limited the development of standardized treatment methods. This study explores the effectiveness and the reasons for discrepancies in the entity recognition and classification of meridians in acupuncture indication using the Acupuncture Bidirectional Encoder Representations from Transformers (ACUBERT) model. During the research process, we selected 54 593 different entities from 82 acupuncture medical books as the pretraining corpus for medical literature, conducting classification research on Chinese medical literature using the BERT model. Additionally, we employed the support vector machine and Random Forest models as comparative benchmarks and optimized them through parameter tuning, ultimately leading

SUBMITTER: Xu T 

PROVIDER: S-EPMC11363959 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature