795 related articles for article (PubMed ID: 35321705)
1. Extracting clinical named entity for pituitary adenomas from Chinese electronic medical records.
Fang A; Hu J; Zhao W; Feng M; Fu J; Feng S; Lou P; Ren H; Chen X
BMC Med Inform Decis Mak; 2022 Mar; 22(1):72. PubMed ID: 35321705
[TBL] [Abstract][Full Text] [Related]
2. A deep learning model incorporating part of speech and self-matching attention for named entity recognition of Chinese electronic medical records.
Cai X; Dong S; Hu J
BMC Med Inform Decis Mak; 2019 Apr; 19(Suppl 2):65. PubMed ID: 30961622
[TBL] [Abstract][Full Text] [Related]
3. Extracting comprehensive clinical information for breast cancer using deep learning methods.
Zhang X; Zhang Y; Zhang Q; Ren Y; Qiu T; Ma J; Sun Q
Int J Med Inform; 2019 Dec; 132():103985. PubMed ID: 31627032
[TBL] [Abstract][Full Text] [Related]
4. Clinical Named Entity Recognition From Chinese Electronic Health Records via Machine Learning Methods.
Zhang Y; Wang X; Hou Z; Li J
JMIR Med Inform; 2018 Dec; 6(4):e50. PubMed ID: 30559093
[TBL] [Abstract][Full Text] [Related]
5. Use of BERT (Bidirectional Encoder Representations from Transformers)-Based Deep Learning Method for Extracting Evidences in Chinese Radiology Reports: Development of a Computer-Aided Liver Cancer Diagnosis Framework.
Liu H; Zhang Z; Xu Y; Wang N; Huang Y; Yang Z; Jiang R; Chen H
J Med Internet Res; 2021 Jan; 23(1):e19689. PubMed ID: 33433395
[TBL] [Abstract][Full Text] [Related]
6. An attention-based deep learning model for clinical named entity recognition of Chinese electronic medical records.
Li L; Zhao J; Hou L; Zhai Y; Shi J; Cui F
BMC Med Inform Decis Mak; 2019 Dec; 19(Suppl 5):235. PubMed ID: 31801540
[TBL] [Abstract][Full Text] [Related]
7. A hybrid approach for named entity recognition in Chinese electronic medical record.
Ji B; Liu R; Li S; Yu J; Wu Q; Tan Y; Wu J
BMC Med Inform Decis Mak; 2019 Apr; 19(Suppl 2):64. PubMed ID: 30961597
[TBL] [Abstract][Full Text] [Related]
8. Chinese Clinical Named Entity Recognition From Electronic Medical Records Based on Multisemantic Features by Using Robustly Optimized Bidirectional Encoder Representation From Transformers Pretraining Approach Whole Word Masking and Convolutional Neural Networks: Model Development and Validation.
Wang W; Li X; Ren H; Gao D; Fang A
JMIR Med Inform; 2023 May; 11():e44597. PubMed ID: 37163343
[TBL] [Abstract][Full Text] [Related]
9. Comparing Different Methods for Named Entity Recognition in Portuguese Neurology Text.
Lopes F; Teixeira C; Gonçalo Oliveira H
J Med Syst; 2020 Feb; 44(4):77. PubMed ID: 32112285
[TBL] [Abstract][Full Text] [Related]
10. Named entity recognition from Chinese adverse drug event reports with lexical feature based BiLSTM-CRF and tri-training.
Chen Y; Zhou C; Li T; Wu H; Zhao X; Ye K; Liao J
J Biomed Inform; 2019 Aug; 96():103252. PubMed ID: 31323311
[TBL] [Abstract][Full Text] [Related]
11. Named entity recognition of Chinese electronic medical records based on a hybrid neural network and medical MC-BERT.
Chen P; Zhang M; Yu X; Li S
BMC Med Inform Decis Mak; 2022 Dec; 22(1):315. PubMed ID: 36457119
[TBL] [Abstract][Full Text] [Related]
12. Research on named entity recognition of Traditional Chinese Medicine chest discomfort cases incorporating domain vocabulary features.
Liu Q; Zhang L; Ren G; Zou B
Comput Biol Med; 2023 Nov; 166():107466. PubMed ID: 37742417
[TBL] [Abstract][Full Text] [Related]
13. An imConvNet-based deep learning model for Chinese medical named entity recognition.
Zheng Y; Han Z; Cai Y; Duan X; Sun J; Yang W; Huang H
BMC Med Inform Decis Mak; 2022 Nov; 22(1):303. PubMed ID: 36411432
[TBL] [Abstract][Full Text] [Related]
14. Chinese-Named Entity Recognition From Adverse Drug Event Records: Radical Embedding-Combined Dynamic Embedding-Based BERT in a Bidirectional Long Short-term Conditional Random Field (Bi-LSTM-CRF) Model.
Wu H; Ji J; Tian H; Chen Y; Ge W; Zhang H; Yu F; Zou J; Nakamura M; Liao J
JMIR Med Inform; 2021 Dec; 9(12):e26407. PubMed ID: 34855616
[TBL] [Abstract][Full Text] [Related]
15. Chinese clinical named entity recognition via multi-head self-attention based BiLSTM-CRF.
An Y; Xia X; Chen X; Wu FX; Wang J
Artif Intell Med; 2022 May; 127():102282. PubMed ID: 35430042
[TBL] [Abstract][Full Text] [Related]
16. Automatic knowledge extraction from Chinese electronic medical records and rheumatoid arthritis knowledge graph construction.
Liu F; Liu M; Li M; Xin Y; Gao D; Wu J; Zhu J
Quant Imaging Med Surg; 2023 Jun; 13(6):3873-3890. PubMed ID: 37284084
[TBL] [Abstract][Full Text] [Related]
17. Chinese clinical named entity recognition with radical-level feature and self-attention mechanism.
Yin M; Mou C; Xiong K; Ren J
J Biomed Inform; 2019 Oct; 98():103289. PubMed ID: 31541715
[TBL] [Abstract][Full Text] [Related]
18. A fine-grained Chinese word segmentation and part-of-speech tagging corpus for clinical text.
Xiong Y; Wang Z; Jiang D; Wang X; Chen Q; Xu H; Yan J; Tang B
BMC Med Inform Decis Mak; 2019 Apr; 19(Suppl 2):66. PubMed ID: 30961602
[TBL] [Abstract][Full Text] [Related]
19. Data governance and Gensini score automatic calculation for coronary angiography with deep-learning-based natural language extraction.
Li F; Jiang M; Xu H; Chen Y; Chen F; Nie W; Wang L
Math Biosci Eng; 2024 Feb; 21(3):4085-4103. PubMed ID: 38549319
[TBL] [Abstract][Full Text] [Related]
20. Medical Named Entity Extraction from Chinese Resident Admit Notes Using Character and Word Attention-Enhanced Neural Network.
Gao Y; Wang Y; Wang P; Gu L
Int J Environ Res Public Health; 2020 Mar; 17(5):. PubMed ID: 32131522
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
