144 related articles for article (PubMed ID: 33936450)
1. Neural Multi-Task Learning for Adverse Drug Reaction Extraction.
Liu F; Zheng X; Yu H; Tjia J
AMIA Annu Symp Proc; 2020; 2020():756-762. PubMed ID: 33936450
[TBL] [Abstract][Full Text] [Related]
2. Machine learning-based identification and rule-based normalization of adverse drug reactions in drug labels.
Tiftikci M; Özgür A; He Y; Hur J
BMC Bioinformatics; 2019 Dec; 20(Suppl 21):707. PubMed ID: 31865904
[TBL] [Abstract][Full Text] [Related]
3. Artificial intelligence-powered pharmacovigilance: A review of machine and deep learning in clinical text-based adverse drug event detection for benchmark datasets.
Li Y; Tao W; Li Z; Sun Z; Li F; Fenton S; Xu H; Tao C
J Biomed Inform; 2024 Apr; 152():104621. PubMed ID: 38447600
[TBL] [Abstract][Full Text] [Related]
4. Deep learning approaches for extracting adverse events and indications of dietary supplements from clinical text.
Fan Y; Zhou S; Li Y; Zhang R
J Am Med Inform Assoc; 2021 Mar; 28(3):569-577. PubMed ID: 33150942
[TBL] [Abstract][Full Text] [Related]
5. Position-aware deep multi-task learning for drug-drug interaction extraction.
Zhou D; Miao L; He Y
Artif Intell Med; 2018 May; 87():1-8. PubMed ID: 29559249
[TBL] [Abstract][Full Text] [Related]
6. Extracting entities with attributes in clinical text via joint deep learning.
Shi X; Yi Y; Xiong Y; Tang B; Chen Q; Wang X; Ji Z; Zhang Y; Xu H
J Am Med Inform Assoc; 2019 Dec; 26(12):1584-1591. PubMed ID: 31550346
[TBL] [Abstract][Full Text] [Related]
7. A two-stage deep learning approach for extracting entities and relationships from medical texts.
Suárez-Paniagua V; Rivera Zavala RM; Segura-Bedmar I; Martínez P
J Biomed Inform; 2019 Nov; 99():103285. PubMed ID: 31546016
[TBL] [Abstract][Full Text] [Related]
8. SSEL-ADE: A semi-supervised ensemble learning framework for extracting adverse drug events from social media.
Liu J; Zhao S; Wang G
Artif Intell Med; 2018 Jan; 84():34-49. PubMed ID: 29111222
[TBL] [Abstract][Full Text] [Related]
9. Active learning for ontological event extraction incorporating named entity recognition and unknown word handling.
Han X; Kim JJ; Kwoh CK
J Biomed Semantics; 2016; 7():22. PubMed ID: 27127603
[TBL] [Abstract][Full Text] [Related]
10. An adverse drug effect mentions extraction method based on weighted online recurrent extreme learning machine.
El-Allaly ED; Sarrouti M; En-Nahnahi N; Ouatik El Alaoui S
Comput Methods Programs Biomed; 2019 Jul; 176():33-41. PubMed ID: 31200909
[TBL] [Abstract][Full Text] [Related]
11. A study of deep learning approaches for medication and adverse drug event extraction from clinical text.
Wei Q; Ji Z; Li Z; Du J; Wang J; Xu J; Xiang Y; Tiryaki F; Wu S; Zhang Y; Tao C; Xu H
J Am Med Inform Assoc; 2020 Jan; 27(1):13-21. PubMed ID: 31135882
[TBL] [Abstract][Full Text] [Related]
12. HITSZ_CDR: an end-to-end chemical and disease relation extraction system for BioCreative V.
Li H; Tang B; Chen Q; Chen K; Wang X; Wang B; Wang Z
Database (Oxford); 2016; 2016():. PubMed ID: 27270713
[TBL] [Abstract][Full Text] [Related]
13. Adverse drug events and medication relation extraction in electronic health records with ensemble deep learning methods.
Christopoulou F; Tran TT; Sahu SK; Miwa M; Ananiadou S
J Am Med Inform Assoc; 2020 Jan; 27(1):39-46. PubMed ID: 31390003
[TBL] [Abstract][Full Text] [Related]
14. A neural network multi-task learning approach to biomedical named entity recognition.
Crichton G; Pyysalo S; Chiu B; Korhonen A
BMC Bioinformatics; 2017 Aug; 18(1):368. PubMed ID: 28810903
[TBL] [Abstract][Full Text] [Related]
15. Biomedical named entity recognition using deep neural networks with contextual information.
Cho H; Lee H
BMC Bioinformatics; 2019 Dec; 20(1):735. PubMed ID: 31881938
[TBL] [Abstract][Full Text] [Related]
16. A Text Mining Pipeline Using Active and Deep Learning Aimed at Curating Information in Computational Neuroscience.
Shardlow M; Ju M; Li M; O'Reilly C; Iavarone E; McNaught J; Ananiadou S
Neuroinformatics; 2019 Jul; 17(3):391-406. PubMed ID: 30443819
[TBL] [Abstract][Full Text] [Related]
17. Combining relation extraction with function detection for BEL statement extraction.
Liu S; Cheng W; Qian L; Zhou G
Database (Oxford); 2019 Jan; 2019():. PubMed ID: 30624649
[TBL] [Abstract][Full Text] [Related]
18. Chemical named entity recognition in patents by domain knowledge and unsupervised feature learning.
Zhang Y; Xu J; Chen H; Wang J; Wu Y; Prakasam M; Xu H
Database (Oxford); 2016; 2016():. PubMed ID: 27087307
[TBL] [Abstract][Full Text] [Related]
19. DTranNER: biomedical named entity recognition with deep learning-based label-label transition model.
Hong SK; Lee JG
BMC Bioinformatics; 2020 Feb; 21(1):53. PubMed ID: 32046638
[TBL] [Abstract][Full Text] [Related]
20. A neural joint model for entity and relation extraction from biomedical text.
Li F; Zhang M; Fu G; Ji D
BMC Bioinformatics; 2017 Mar; 18(1):198. PubMed ID: 28359255
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
