[1] |
杨威, 刘艳如, 孟颖 ,等. 浅谈临床医学术语的标准化管理[J]. 中国卫生标准管理, 2021,12(12): 1-4.
|
|
YANG W , LIU Y R , MENG Y ,et al. Discussion on standardization management of clinical medical terminology[J]. China Health Standard Management, 2021,12(12): 1-4.
|
[2] |
赵嘉莹, 高鹏, 朱勇俊 ,等. 人工智能的应用将改进中国基层医疗卫生服务效能[J]. 中国全科医学, 2017,20(34): 4219-4223.
|
|
ZHAO J Y , GAO P , ZHU Y J ,et al. The application of artificial intelligence could improve primary health care provision in China[J]. Chinese General Practice, 2017,20(24): 4219-4223.
|
[3] |
曾晓天, 徐春园, 张勇 ,等. 人工智能在医学大数据标准化体系建设中的研究进展[J]. 北京生物医学工程, 2019,38(6): 639-643.
|
|
ZENG X T , XU C Y , ZHANG Y ,et al. Research progress on artificial intelligence in the standardization system construction of medical big data[J]. Beijing Biomedical Engineering, 2019,38(6): 640-644.
|
[4] |
郑强, 刘齐军, 王正华 ,等. 生物医学命名实体识别的研究与进展[J]. 计算机应用研究, 2010,27(3): 811-815,832.
|
|
ZHENG Q , LIU Q J , WANG Z H ,et al. Research and development on biomedical named entity recognition[J]. Application Research of Computers, 2010,27(3): 811-815,832.
|
[5] |
SETTLES B . Active learning literature survey[J]. Machine Learning, 2010,15(2): 201-221.
|
[6] |
HANISCH D , FUNDEL K , MEVISSEN H T ,et al. ProMiner:rule-based protein and gene entity recognition[J]. BMC Bioinformatics, 2005,6(Suppl 1): S14.
|
[7] |
刘一佳, 车万翔, 刘挺 ,等. 基于序列标注的中文分词,词性标注模型比较分析[C]// 第六届全国青年计算语言学会议论文集. [出版者不详:出版地不详], 2012: 26-34.
|
|
LIU Y J , CHE W X , LIU T ,et al. A comparison study of sequence labeling methods for Chinese word segmentation,POS tagging models[C]// The 6th Youth Conference of Computational Linguistics.[S.l.:s.n.], 2012: 26-34.
|
[8] |
王浩畅, 赵铁军 . 基于SVM的生物医学命名实体的识别[J]. 哈尔滨工程大学学报, 2006,27(S1): 570-574.
|
|
WANG H C , ZHAO T J . SVM-based biomedical Name entity recognition[J]. Journal of Harbin Engineering University, 2006,27(S1): 570-574.
|
[9] |
MORWAL S , CHOPRA D . NERHMM:a tool for named entity recognition based on hidden Markov model[J]. International Journal on Natural Language Computing, 2013,2(2): 43-49.
|
[10] |
PATIL N , PATIL A , PAWAR B V . Named entity recognition using conditional random fields[J]. Procedia Computer Science, 2020,167: 1181-1188.
|
[11] |
LAMPLE G , BALLESTEROS M , SUBRAMANIAN S ,et al. Neural architectures for named entity recognition[C]// Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics:Human Language Technologies. Stroudsburg:Association for Computational Linguistics, 2016.
|
[12] |
OUYANG E , LI Y X , JIN L ,et al. Exploring N-gram character presentation in bidirectional RNN-CRF for Chinese clinical named entity recognition[C]// Proceedings of China Conference on Knowledge Graph and Semantic Computing 2017.[S.l.:s.n.], 2017.
|
[13] |
DONG X S , CHOWDHURY S , QIAN L J ,et al. Transfer bi-directional LSTM RNN for named entity recognition in Chinese electronic medical records[C]// Proceedings of 2017 IEEE 19th International Conference on e-Health Networking,Applications and Services. Piscataway:IEEE Press, 2017: 1-4.
|
[14] |
ZHANG Z C , ZHANG Y , ZHOU T . Medical knowledge attention enhanced neural model for named entity recognition in Chinese EMR[C]// Proceedings of China National Conference on Chinese Computational Linguistics,International Symposium on Natural Language Processing Based on Naturally Annotated Big Data. Cham:Springer, 2018: 376-385.
|
[15] |
WANG Q , XIA Y H , ZHOU Y M ,et al. Incorporating dictionaries into deep neural networks for the Chinese clinical named entity recognition[J]. Journal of Biomedical Informatics, 2019,92:103133.
|
[16] |
QIU J H , WANG Q , ZHOU Y M ,et al. Fast and accurate recognition of Chinese clinical named entities with residual dilated convolutions[C]// Proceedings of 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). Piscataway:IEEE Press, 2019: 935-942.
|
[17] |
LI X Y , ZHANG H , ZHOU X H . Chinese clinical named entity recognition with variant neural structures based on BERT methods[J]. Journal of Biomedical Informatics, 2020,107:103422.
|
[18] |
张岑芳 . 基于主动学习的命名实体识别算法[J]. 计算机与现代化, 2021(7): 18-22.
|
|
ZHANG C F . Named entity recognition algorithm based on active learning[J]. Computer and Modernization, 2021(7): 18-22.
|
[19] |
卢宁杰 . 结合主动学习的中文医疗命名实体识别研究[D]. 上海:华东师范大学, 2020.
|
|
LU N J . Research on Chinese medical named entity recognition combined with active learning[D]. Shanghai:East China Normal University, 2020.
|
[20] |
SHANNON C E . A mathematical theory of communication[J]. Bell System Technical Journal, 1948,27(4): 623-656.
|
[21] |
LEWIS D D , CATLETT J . Heterogeneous uncertainty sampling for supervised learning[M]// Machine learning proceedings 1994. Amsterdam: Elsevier, 1994: 148-156.
|
[22] |
SCHEFFER T , DECOMAIN C , WROBEL S . Active hidden Markov models for information extraction[M]// Advances in intelligent data analysis. Heidelberg: Springer, 2001: 309-318.
|
[23] |
DEVLIN J , CHANG M , LEE K ,et al. BERT:pre-training of deep bidirectional transformers for language understanding[J]. arXiv preprint. 2018:arXiv:1810.04805.
|
[24] |
GRAVES A , SCHMIDHUBER J . Framewise phoneme classification with bidirectional LSTM and other neural network architectures[J]. Neural Networks, 2005,18(5/6): 602-610.
|
[25] |
SUTTON C . An introduction to conditional random fields[J]. Foundations and Trends? in Machine Learning, 2012,4(4): 267-373.
|
[26] |
KINGMA D P , BA J . Adam:a method for stochastic optimization[J]. arXiv preprint,2014,arXiv:1412. 6980.
|
[27] |
ZAN H Y , LI W X , ZHANG K L ,et al. Building a pediatric medical corpus:word segmentation and named entity annotation[M]// Lecture notes in computer science. Cham: Springer, 2021: 652-664.
|
[28] |
LAN Z , CHEN M , GOODMAN S ,et al. ALBERT:a lite BERT for self-supervised learning of language representations[J]. arXiv preprint, 2019,arXiv:1909.11942.
|
[29] |
DIAO S Z , BAI J X , SONG Y ,et al. ZEN:pre-training Chinese text encoder enhanced by N-gram representations[C]// Proceedings of Findings of the Association for Computational Linguistics:EMNLP 2020. Stroudsburg:Association for Computational Linguistics, 2020.
|