182 related articles for article (PubMed ID: 24559132)
1. A pipeline to extract drug-adverse event pairs from multiple data sources.
Yeleswarapu S; Rao A; Joseph T; Saipradeep VG; Srinivasan R
BMC Med Inform Decis Mak; 2014 Feb; 14():13. PubMed ID: 24559132
[TBL] [Abstract][Full Text] [Related]
2. Pattern mining for extraction of mentions of Adverse Drug Reactions from user comments.
Nikfarjam A; Gonzalez GH
AMIA Annu Symp Proc; 2011; 2011():1019-26. PubMed ID: 22195162
[TBL] [Abstract][Full Text] [Related]
3. 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]
4. Utility of social media and crowd-intelligence data for pharmacovigilance: a scoping review.
Tricco AC; Zarin W; Lillie E; Jeblee S; Warren R; Khan PA; Robson R; Pham B; Hirst G; Straus SE
BMC Med Inform Decis Mak; 2018 Jun; 18(1):38. PubMed ID: 29898743
[TBL] [Abstract][Full Text] [Related]
5. Signal detection of human papillomavirus vaccines using the Korea Adverse Events Reporting System database, between 2005 and 2016.
Ran J; Yang JY; Lee JH; Kim HJ; Choi JY; Shin JY
Int J Clin Pharm; 2019 Oct; 41(5):1365-1372. PubMed ID: 31313003
[TBL] [Abstract][Full Text] [Related]
6. A Pharmacovigilance Signaling System Based on FDA Regulatory Action and Post-Marketing Adverse Event Reports.
Hoffman KB; Dimbil M; Tatonetti NP; Kyle RF
Drug Saf; 2016 Jun; 39(6):561-75. PubMed ID: 26946292
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. On the creation of a clinical gold standard corpus in Spanish: Mining adverse drug reactions.
Oronoz M; Gojenola K; Pérez A; de Ilarraza AD; Casillas A
J Biomed Inform; 2015 Aug; 56():318-32. PubMed ID: 26141794
[TBL] [Abstract][Full Text] [Related]
9. Large-scale automatic extraction of side effects associated with targeted anticancer drugs from full-text oncological articles.
Xu R; Wang Q
J Biomed Inform; 2015 Jun; 55():64-72. PubMed ID: 25817969
[TBL] [Abstract][Full Text] [Related]
10. Evaluation of Natural Language Processing (NLP) systems to annotate drug product labeling with MedDRA terminology.
Ly T; Pamer C; Dang O; Brajovic S; Haider S; Botsis T; Milward D; Winter A; Lu S; Ball R
J Biomed Inform; 2018 Jul; 83():73-86. PubMed ID: 29860093
[TBL] [Abstract][Full Text] [Related]
11. Algorithmic Identification of Treatment-Emergent Adverse Events From Clinical Notes Using Large Language Models: A Pilot Study in Inflammatory Bowel Disease.
Silverman AL; Sushil M; Bhasuran B; Ludwig D; Buchanan J; Racz R; Parakala M; El-Kamary S; Ahima O; Belov A; Choi L; Billings M; Li Y; Habal N; Liu Q; Tiwari J; Butte AJ; Rudrapatna VA
Clin Pharmacol Ther; 2024 Jun; 115(6):1391-1399. PubMed ID: 38459719
[TBL] [Abstract][Full Text] [Related]
12. Using text-mining techniques in electronic patient records to identify ADRs from medicine use.
Warrer P; Hansen EH; Juhl-Jensen L; Aagaard L
Br J Clin Pharmacol; 2012 May; 73(5):674-84. PubMed ID: 22122057
[TBL] [Abstract][Full Text] [Related]
13. Automatic detection of adverse events to predict drug label changes using text and data mining techniques.
Gurulingappa H; Toldo L; Rajput AM; Kors JA; Taweel A; Tayrouz Y
Pharmacoepidemiol Drug Saf; 2013 Nov; 22(11):1189-94. PubMed ID: 23935003
[TBL] [Abstract][Full Text] [Related]
14. A drug-adverse event extraction algorithm to support pharmacovigilance knowledge mining from PubMed citations.
Wang W; Haerian K; Salmasian H; Harpaz R; Chase H; Friedman C
AMIA Annu Symp Proc; 2011; 2011():1464-70. PubMed ID: 22195210
[TBL] [Abstract][Full Text] [Related]
15. Mining association patterns of drug-interactions using post marketing FDA's spontaneous reporting data.
Ibrahim H; Saad A; Abdo A; Sharaf Eldin A
J Biomed Inform; 2016 Apr; 60():294-308. PubMed ID: 26903152
[TBL] [Abstract][Full Text] [Related]
16. From narrative descriptions to MedDRA: automagically encoding adverse drug reactions.
Combi C; Zorzi M; Pozzani G; Moretti U; Arzenton E
J Biomed Inform; 2018 Aug; 84():184-199. PubMed ID: 29981491
[TBL] [Abstract][Full Text] [Related]
17. Exploring Spanish health social media for detecting drug effects.
Segura-Bedmar I; Martínez P; Revert R; Moreno-Schneider J
BMC Med Inform Decis Mak; 2015; 15 Suppl 2(Suppl 2):S6. PubMed ID: 26100267
[TBL] [Abstract][Full Text] [Related]
18. 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]
19. Pediatric drug safety signal detection: a new drug-event reference set for performance testing of data-mining methods and systems.
Osokogu OU; Fregonese F; Ferrajolo C; Verhamme K; de Bie S; 't Jong G; Catapano M; Weibel D; Kaguelidou F; Bramer WM; Hsia Y; Wong IC; Gazarian M; Bonhoeffer J; Sturkenboom M
Drug Saf; 2015 Feb; 38(2):207-17. PubMed ID: 25663078
[TBL] [Abstract][Full Text] [Related]
20. Prospective Evaluation of Adverse Event Recognition Systems in Twitter: Results from the Web-RADR Project.
Gattepaille LM; Hedfors Vidlin S; Bergvall T; Pierce CE; Ellenius J
Drug Saf; 2020 Aug; 43(8):797-808. PubMed ID: 32410156
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]