These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

141 related articles for article (PubMed ID: 20362071)

  • 1. Selecting information in electronic health records for knowledge acquisition.
    Wang X; Chase H; Markatou M; Hripcsak G; Friedman C
    J Biomed Inform; 2010 Aug; 43(4):595-601. PubMed ID: 20362071
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Automated knowledge acquisition from clinical narrative reports.
    Wang X; Chused A; Elhadad N; Friedman C; Markatou M
    AMIA Annu Symp Proc; 2008 Nov; 2008():783-7. PubMed ID: 18999156
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Characterizing environmental and phenotypic associations using information theory and electronic health records.
    Wang X; Hripcsak G; Friedman C
    BMC Bioinformatics; 2009 Sep; 10 Suppl 9(Suppl 9):S13. PubMed ID: 19761567
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Leveraging Contextual Information in Extracting Long Distance Relations from Clinical Notes.
    Guan H; Devarakonda M
    AMIA Annu Symp Proc; 2019; 2019():1051-1060. PubMed ID: 32308902
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Natural Language Processing for EHR-Based Pharmacovigilance: A Structured Review.
    Luo Y; Thompson WK; Herr TM; Zeng Z; Berendsen MA; Jonnalagadda SR; Carson MB; Starren J
    Drug Saf; 2017 Nov; 40(11):1075-1089. PubMed ID: 28643174
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Adverse drug event and medication extraction in electronic health records via a cascading architecture with different sequence labeling models and word embeddings.
    Dai HJ; Su CH; Wu CS
    J Am Med Inform Assoc; 2020 Jan; 27(1):47-55. PubMed ID: 31334805
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Automated acquisition of disease drug knowledge from biomedical and clinical documents: an initial study.
    Chen ES; Hripcsak G; Xu H; Markatou M; Friedman C
    J Am Med Inform Assoc; 2008; 15(1):87-98. PubMed ID: 17947625
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Extracting medications and associated adverse drug events using a natural language processing system combining knowledge base and deep learning.
    Chen L; Gu Y; Ji X; Sun Z; Li H; Gao Y; Huang Y
    J Am Med Inform Assoc; 2020 Jan; 27(1):56-64. PubMed ID: 31591641
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Adverse drug event detection using natural language processing: A scoping review of supervised learning methods.
    Murphy RM; Klopotowska JE; de Keizer NF; Jager KJ; Leopold JH; Dongelmans DA; Abu-Hanna A; Schut MC
    PLoS One; 2023; 18(1):e0279842. PubMed ID: 36595517
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Adverse drug event rates in pediatric pulmonary hypertension: a comparison of real-world data sources.
    Geva A; Abman SH; Manzi SF; Ivy DD; Mullen MP; Griffin J; Lin C; Savova GK; Mandl KD
    J Am Med Inform Assoc; 2020 Feb; 27(2):294-300. PubMed ID: 31769835
    [TBL] [Abstract][Full Text] [Related]  

  • 11. 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]  

  • 12. Active computerized pharmacovigilance using natural language processing, statistics, and electronic health records: a feasibility study.
    Wang X; Hripcsak G; Markatou M; Friedman C
    J Am Med Inform Assoc; 2009; 16(3):328-37. PubMed ID: 19261932
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Adverse drug event notification on a semantic interoperability framework.
    Krahn T; Eichelberg M; Müller F; Gönül S; Laleci Erturkmen GB; Sinaci AA; Appelrath HJ
    Stud Health Technol Inform; 2014; 205():111-5. PubMed ID: 25160156
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Structuring Legacy Pathology Reports by openEHR Archetypes to Enable Semantic Querying.
    Kropf S; Krücken P; Mueller W; Denecke K
    Methods Inf Med; 2017 May; 56(3):230-237. PubMed ID: 28244546
    [TBL] [Abstract][Full Text] [Related]  

  • 15. 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]  

  • 16. MADEx: A System for Detecting Medications, Adverse Drug Events, and Their Relations from Clinical Notes.
    Yang X; Bian J; Gong Y; Hogan WR; Wu Y
    Drug Saf; 2019 Jan; 42(1):123-133. PubMed ID: 30600484
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Temporal reasoning with medical data--a review with emphasis on medical natural language processing.
    Zhou L; Hripcsak G
    J Biomed Inform; 2007 Apr; 40(2):183-202. PubMed ID: 17317332
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Ensemble method-based extraction of medication and related information from clinical texts.
    Kim Y; Meystre SM
    J Am Med Inform Assoc; 2020 Jan; 27(1):31-38. PubMed ID: 31282932
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Detecting adverse drug reactions in discharge summaries of electronic medical records using Readpeer.
    Tang Y; Yang J; Ang PS; Dorajoo SR; Foo B; Soh S; Tan SH; Tham MY; Ye Q; Shek L; Sung C; Tung A
    Int J Med Inform; 2019 Aug; 128():62-70. PubMed ID: 31160013
    [TBL] [Abstract][Full Text] [Related]  

  • 20. 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]  

    [Next]    [New Search]
    of 8.