Automated information extraction model enhancing traditional Chinese medicine RCT evidence extraction (Evi-BERT): algorithm development and validation

Our work provided an intelligent approach to extracting clinical evidence for TCM RCT data. Our model can help physicians reduce the time spent reading journals and rapidly speed up the screening of clinical trial evidence to help generate accurate clinical reference guidelines. Additionally, we hope the structured clinical evidence and structured knowledge extracted from this study will help other researchers build large language models in TCM.

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Publication Details

Journal
Frontiers in Artificial Intelligence
Published
2024-08-15
DOI
https://doi.org/10.3389/frai.2024.1454945
Citations
6
Primary Topic
Biomedical Text Mining and Ontologies
Type
article
Field-Weighted Citation Impact
1.40
Controls
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article

Automated information extraction model enhancing traditional Chinese medicine RCT evidence extraction (Evi-BERT): algorithm development and validation

Dongran Han, Heyuan Liu, Zhongzhi Luan, Yixing Liu et al.
6 citations
Frontiers in Artificial Intelligence
Biomedical Text Mining and Ontologies
1.40
article

Automated information extraction model enhancing traditional Chinese medicine RCT evidence extraction (Evi-BERT): algorithm development and validation

Dongran Han, Heyuan Liu, Zhongzhi Luan, Yixing Liu, Jiaxing Qi, Yizhen Li
article en
6 citations

Abstract

Our work provided an intelligent approach to extracting clinical evidence for TCM RCT data. Our model can help physicians reduce the time spent reading journals and rapidly speed up the screening of clinical trial evidence to help generate accurate clinical reference guidelines. Additionally, we hope the structured clinical evidence and structured knowledge extracted from this study will help other researchers build large language models in TCM.

Frontiers in Artificial IntelligenceVol. 7
Beijing University of Chinese Medicine (CN), Beihang University (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 19%
Biomedical Text Mining and Ontologies
1.40
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