Deep learning-based large-scale named entity recognition for anatomical region of mammalian brain-Reference-Cited by-同舟云学术

Deep learning-based large-scale named entity recognition for anatomical region of mammalian brain

Published:2022 Issue:3 Volume:10 Page:253
ISSN:2095-4689
Container-title:Quantitative Biology
language:en
Short-container-title:Quant. Biol.

Author:

Chai Xiaokang,Di Yachao,Feng Zhao,Guan Yue,Zhang Guoqing,Li Anan,Luo Qingming

Publisher

China Engineering Science Press Co. Ltd.

Subject

Applied Mathematics,Computer Science Applications,Biochemistry, Genetics and Molecular Biology (miscellaneous),Modeling and Simulation

Reference27 articles.

1. $lt;span class='magtech_ref_source'$gt; L., Sun, R., Patel, J., Liu, K., Chen, T., Wu, J. Li, ( 2009). Mining brain region connectivity for Alzheimer’s disease study via sparse inverse covariance estimation. In: Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1335– 1344$lt;/span$gt;

2. $lt;span class='magtech_ref_source'$gt; E. F. Sang, ( 2003). Introduction to the CoNLL -2003 shared task: Language-independent named entity recognition. In: Proceedings of the Seventh Conference on Natural Language Learning at HLT-NAACL 2003, pp. 142– 147$lt;/span$gt;

3. $lt;span class='magtech_ref_source'$gt; X., Wang, Y., Zhang, X., Ren, Y., Zhang, M., Zitnik, J., Shang, C. Langlotz, ( 2019). Cross-type biomedical named entity recognition with deep multi-task learning. Bioinformatics, 35 : 1745– 1752 $lt;/span$gt;

4. $lt;span class='magtech_ref_source'$gt; W., Yoon, C. H., So, J. Lee, ( 2019). CollaboNet: collaboration of deep neural networks for biomedical named entity recognition. BMC Bioinformatics, 20 : 249 $lt;/span$gt;

5. $lt;span class='magtech_ref_source'$gt; M., Cho, J., Ha, C. Park, ( 2020). Combinatorial feature embedding based on CNN and LSTM for biomedical named entity recognition. J. Biomed. Inform., 103 : 103381 $lt;/span$gt;