NERBio: using selected word conjunctions, term normalization, and global patterns to improve biomedical named entity recognition
<p>Abstract</p> <p>Background</p> <p>Biomedical named entity recognition (Bio-NER) is a challenging problem because, in general, biomedical named entities of the same category (e.g., proteins and genes) do not follow one standard nomenclature. They have many irregularit...
Main Authors: | Hung Hsieh-Chuan, Dai Hong-Jie, Sung Cheng-Lung, Tsai Richard, Sung Ting-Yi, Hsu Wen-Lian |
---|---|
Format: | Article |
Language: | English |
Published: |
BMC
2006-12-01
|
Series: | BMC Bioinformatics |
Online Access: | http://dx.doi.org/10.1186/1471-2105-7-S5-S11 |
Similar Items
-
Various criteria in the evaluation of biomedical named entity recognition
by: Lin Yu-Chun, et al.
Published: (2006-02-01) -
Comparing general and specialized word embeddings for biomedical named entity recognition
by: Rigo E. Ramos-Vargas, et al.
Published: (2021-02-01) -
A Neural Named Entity Recognition and Multi-Type Normalization Tool for Biomedical Text Mining
by: Donghyeon Kim, et al.
Published: (2019-01-01) -
Knowledge-enhanced biomedical named entity recognition and normalization: application to proteins and genes
by: Huiwei Zhou, et al.
Published: (2020-01-01) -
Analyzing transfer learning impact in biomedical cross-lingual named entity recognition and normalization
by: Renzo M. Rivera-Zavala, et al.
Published: (2021-12-01)