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Items: 1 to 20 of 101

2.
3.

ADEpedia 2.0: Integration of Normalized Adverse Drug Events (ADEs) Knowledge from the UMLS.

Jiang G, Liu H, Solbrig HR, Chute CG.

AMIA Jt Summits Transl Sci Proc. 2013 Mar 18;2013:100-4.

4.

Mining severe drug-drug interaction adverse events using Semantic Web technologies: a case study.

Jiang G, Liu H, Solbrig HR, Chute CG.

BioData Min. 2015 Mar 25;8:12. doi: 10.1186/s13040-015-0044-6.

5.

Building a knowledge base of severe adverse drug events based on AERS reporting data using semantic web technologies.

Jiang G, Wang L, Liu H, Solbrig HR, Chute CG.

Stud Health Technol Inform. 2013;192:496-500.

PMID:
23920604
6.

Adverse drug events: database construction and in silico prediction.

Cheng F, Li W, Wang X, Zhou Y, Wu Z, Shen J, Tang Y.

J Chem Inf Model. 2013 Apr 22;53(4):744-52. doi: 10.1021/ci4000079.

PMID:
23521697
7.

Predicting adverse drug events using pharmacological network models.

Cami A, Arnold A, Manzi S, Reis B.

Sci Transl Med. 2011 Dec 21;3(114):114ra127. doi: 10.1126/scitranslmed.3002774.

8.

Towards pharmacogenomics knowledge discovery with the semantic web.

Dumontier M, Villanueva-Rosales N.

Brief Bioinform. 2009 Mar;10(2):153-63. doi: 10.1093/bib/bbn056.

PMID:
19240125
9.

Mining integrated semantic networks for drug repositioning opportunities.

Mullen J, Cockell SJ, Tipney H, Woollard PM, Wipat A.

PeerJ. 2016 Jan 19;4:e1558. doi: 10.7717/peerj.1558.

10.

Using PharmGKB to train text mining approaches for identifying potential gene targets for pharmacogenomic studies.

Pakhomov S, McInnes BT, Lamba J, Liu Y, Melton GB, Ghodke Y, Bhise N, Lamba V, Birnbaum AK.

J Biomed Inform. 2012 Oct;45(5):862-9. doi: 10.1016/j.jbi.2012.04.007.

11.

Network-based analysis reveals distinct association patterns in a semantic MEDLINE-based drug-disease-gene network.

Zhang Y, Tao C, Jiang G, Nair AA, Su J, Chute CG, Liu H.

J Biomed Semantics. 2014 Aug 6;5:33. doi: 10.1186/2041-1480-5-33.

12.

Leveraging graph topology and semantic context for pharmacovigilance through twitter-streams.

Eshleman R, Singh R.

BMC Bioinformatics. 2016 Oct 6;17(Suppl 13):335.

13.

The use of web ontology languages and other semantic web tools in drug discovery.

Chen H, Xie G.

Expert Opin Drug Discov. 2010 May;5(5):413-23. doi: 10.1517/17460441003762709.

PMID:
22823127
14.

Leveraging MEDLINE indexing for pharmacovigilance - Inherent limitations and mitigation strategies.

Winnenburg R, Sorbello A, Ripple A, Harpaz R, Tonning J, Szarfman A, Francis H, Bodenreider O.

J Biomed Inform. 2015 Oct;57:425-35. doi: 10.1016/j.jbi.2015.08.022.

15.

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.

16.

From adverse drug event detection to prevention. A novel clinical decision support framework for medication safety.

Koutkias VG, McNair P, Kilintzis V, Skovhus Andersen K, Ni├Ęs J, Sarfati JC, Ammenwerth E, Chazard E, Jensen S, Beuscart R, Maglaveras N.

Methods Inf Med. 2014;53(6):482-92. doi: 10.3414/ME14-01-0027.

PMID:
25377477
17.

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. doi: 10.1016/j.jbi.2014.07.011.

18.

Hospital admissions caused by adverse drug events: an Australian prospective study.

Phillips AL, Nigro O, Macolino KA, Scarborough KC, Doecke CJ, Angley MT, Shakib S.

Aust Health Rev. 2014 Feb;38(1):51-7. doi: 10.1071/AH12027.

PMID:
24351707
19.
20.

Standardizing adverse drug event reporting data.

Wang L, Jiang G, Li D, Liu H.

J Biomed Semantics. 2014 Aug 12;5:36. doi: 10.1186/2041-1480-5-36.

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