204 related articles for article (PubMed ID: 30010902)
1. Learning predictive models of drug side-effect relationships from distributed representations of literature-derived semantic predications.
Mower J; Subramanian D; Cohen T
J Am Med Inform Assoc; 2018 Oct; 25(10):1339-1350. PubMed ID: 30010902
[TBL] [Abstract][Full Text] [Related]
2. Complementing Observational Signals with Literature-Derived Distributed Representations for Post-Marketing Drug Surveillance.
Mower J; Cohen T; Subramanian D
Drug Saf; 2020 Jan; 43(1):67-77. PubMed ID: 31646442
[TBL] [Abstract][Full Text] [Related]
3. Adverse Drug Event Prediction Using Noisy Literature-Derived Knowledge Graphs: Algorithm Development and Validation.
Dasgupta S; Jayagopal A; Jun Hong AL; Mariappan R; Rajan V
JMIR Med Inform; 2021 Oct; 9(10):e32730. PubMed ID: 34694230
[TBL] [Abstract][Full Text] [Related]
4. Identifying plausible adverse drug reactions using knowledge extracted from the literature.
Shang N; Xu H; Rindflesch TC; Cohen T
J Biomed Inform; 2014 Dec; 52():293-310. PubMed ID: 25046831
[TBL] [Abstract][Full Text] [Related]
5. Embedding of semantic predications.
Cohen T; Widdows D
J Biomed Inform; 2017 Apr; 68():150-166. PubMed ID: 28284761
[TBL] [Abstract][Full Text] [Related]
6. Leveraging graph topology and semantic context for pharmacovigilance through twitter-streams.
Eshleman R; Singh R
BMC Bioinformatics; 2016 Oct; 17(Suppl 13):335. PubMed ID: 27766937
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. Pharmacovigilance from social media: mining adverse drug reaction mentions using sequence labeling with word embedding cluster features.
Nikfarjam A; Sarker A; O'Connor K; Ginn R; Gonzalez G
J Am Med Inform Assoc; 2015 May; 22(3):671-81. PubMed ID: 25755127
[TBL] [Abstract][Full Text] [Related]
9. A comparison of word embeddings for the biomedical natural language processing.
Wang Y; Liu S; Afzal N; Rastegar-Mojarad M; Wang L; Shen F; Kingsbury P; Liu H
J Biomed Inform; 2018 Nov; 87():12-20. PubMed ID: 30217670
[TBL] [Abstract][Full Text] [Related]
10. Augmenting aer2vec: Enriching distributed representations of adverse event report data with orthographic and lexical information.
Ding X; Mower J; Subramanian D; Cohen T
J Biomed Inform; 2021 Jul; 119():103833. PubMed ID: 34111555
[TBL] [Abstract][Full Text] [Related]
11. BioConceptVec: Creating and evaluating literature-based biomedical concept embeddings on a large scale.
Chen Q; Lee K; Yan S; Kim S; Wei CH; Lu Z
PLoS Comput Biol; 2020 Apr; 16(4):e1007617. PubMed ID: 32324731
[TBL] [Abstract][Full Text] [Related]
12. Learning to detect and understand drug discontinuation events from clinical narratives.
Liu F; Pradhan R; Druhl E; Freund E; Liu W; Sauer BC; Cunningham F; Gordon AJ; Peters CB; Yu H
J Am Med Inform Assoc; 2019 Oct; 26(10):943-951. PubMed ID: 31034028
[TBL] [Abstract][Full Text] [Related]
13. A reference standard for evaluation of methods for drug safety signal detection using electronic healthcare record databases.
Coloma PM; Avillach P; Salvo F; Schuemie MJ; Ferrajolo C; Pariente A; Fourrier-Réglat A; Molokhia M; Patadia V; van der Lei J; Sturkenboom M; Trifirò G
Drug Saf; 2013 Jan; 36(1):13-23. PubMed ID: 23315292
[TBL] [Abstract][Full Text] [Related]
14. Classification-by-Analogy: Using Vector Representations of Implicit Relationships to Identify Plausibly Causal Drug/Side-effect Relationships.
Mower J; Subramanian D; Shang N; Cohen T
AMIA Annu Symp Proc; 2016; 2016():1940-1949. PubMed ID: 28269953
[TBL] [Abstract][Full Text] [Related]
15. Assigning factuality values to semantic relations extracted from biomedical research literature.
Kilicoglu H; Rosemblat G; Rindflesch TC
PLoS One; 2017; 12(7):e0179926. PubMed ID: 28678823
[TBL] [Abstract][Full Text] [Related]
16. Unsupervised and self-supervised deep learning approaches for biomedical text mining.
Nadif M; Role F
Brief Bioinform; 2021 Mar; 22(2):1592-1603. PubMed ID: 33569575
[TBL] [Abstract][Full Text] [Related]
17. Deep learning for pharmacovigilance: recurrent neural network architectures for labeling adverse drug reactions in Twitter posts.
Cocos A; Fiks AG; Masino AJ
J Am Med Inform Assoc; 2017 Jul; 24(4):813-821. PubMed ID: 28339747
[TBL] [Abstract][Full Text] [Related]
18. Enhancing the coverage of SemRep using a relation classification approach.
Ming S; Zhang R; Kilicoglu H
J Biomed Inform; 2024 Jul; 155():104658. PubMed ID: 38782169
[TBL] [Abstract][Full Text] [Related]
19. Portable automatic text classification for adverse drug reaction detection via multi-corpus training.
Sarker A; Gonzalez G
J Biomed Inform; 2015 Feb; 53():196-207. PubMed ID: 25451103
[TBL] [Abstract][Full Text] [Related]
20. Mining heterogeneous networks with topological features constructed from patient-contributed content for pharmacovigilance.
Yang CC; Yang H
Artif Intell Med; 2018 Aug; 90():42-52. PubMed ID: 30093253
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
