An ensemble CNN method for biomedical entity normalization
Pan Deng, Haipeng Chen, Mengyao Huang, Xiaowen Ruan, Liang Xu
Abstract
Different representations of the same concept could often be seen in scientific reports and publications. Entity normalization (or entity linking) is the task to match the different representations to their standard concepts. In this paper, we present a two-step ensemble CNN method that normalizes microbiology-related entities in free text to concepts in standard dictionaries. The method is capable of linking entities when only a small microbiology-related biomedical corpus is available for training, and achieved reasonable performance in the online test of the BioNLP-OST19 shared task Bacteria Biotope.- Anthology ID:
- D19-5721
- Volume:
- Proceedings of the 5th Workshop on BioNLP Open Shared Tasks
- Month:
- November
- Year:
- 2019
- Address:
- Hong Kong, China
- Venue:
- BioNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 143–149
- Language:
- URL:
- https://aclanthology.org/D19-5721
- DOI:
- 10.18653/v1/D19-5721
- Cite (ACL):
- Pan Deng, Haipeng Chen, Mengyao Huang, Xiaowen Ruan, and Liang Xu. 2019. An ensemble CNN method for biomedical entity normalization. In Proceedings of the 5th Workshop on BioNLP Open Shared Tasks, pages 143–149, Hong Kong, China. Association for Computational Linguistics.
- Cite (Informal):
- An ensemble CNN method for biomedical entity normalization (Deng et al., BioNLP 2019)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/D19-5721.pdf
- Code
- OXPHOS/BioNLP
- Data
- BB, BB-norm-habitat, BB-norm-phenotype