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 *

892 related articles for article (PubMed ID: 20819853)

  • 1. Mayo clinical Text Analysis and Knowledge Extraction System (cTAKES): architecture, component evaluation and applications.
    Savova GK; Masanz JJ; Ogren PV; Zheng J; Sohn S; Kipper-Schuler KC; Chute CG
    J Am Med Inform Assoc; 2010; 17(5):507-13. PubMed ID: 20819853
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Sophia: A Expedient UMLS Concept Extraction Annotator.
    Divita G; Zeng QT; Gundlapalli AV; Duvall S; Nebeker J; Samore MH
    AMIA Annu Symp Proc; 2014; 2014():467-76. PubMed ID: 25954351
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Towards comprehensive syntactic and semantic annotations of the clinical narrative.
    Albright D; Lanfranchi A; Fredriksen A; Styler WF; Warner C; Hwang JD; Choi JD; Dligach D; Nielsen RD; Martin J; Ward W; Palmer M; Savova GK
    J Am Med Inform Assoc; 2013; 20(5):922-30. PubMed ID: 23355458
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Part-of-speech tagging for clinical text: wall or bridge between institutions?
    Fan JW; Prasad R; Yabut RM; Loomis RM; Zisook DS; Mattison JE; Huang Y
    AMIA Annu Symp Proc; 2011; 2011():382-91. PubMed ID: 22195091
    [TBL] [Abstract][Full Text] [Related]  

  • 5. The 2019 n2c2/OHNLP Track on Clinical Semantic Textual Similarity: Overview.
    Wang Y; Fu S; Shen F; Henry S; Uzuner O; Liu H
    JMIR Med Inform; 2020 Nov; 8(11):e23375. PubMed ID: 33245291
    [TBL] [Abstract][Full Text] [Related]  

  • 6. The Yale cTAKES extensions for document classification: architecture and application.
    Garla V; Lo Re V; Dorey-Stein Z; Kidwai F; Scotch M; Womack J; Justice A; Brandt C
    J Am Med Inform Assoc; 2011; 18(5):614-20. PubMed ID: 21622934
    [TBL] [Abstract][Full Text] [Related]  

  • 7. 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]  

  • 8. A concept-driven biomedical knowledge extraction and visualization framework for conceptualization of text corpora.
    Jahiruddin ; Abulaish M; Dey L
    J Biomed Inform; 2010 Dec; 43(6):1020-35. PubMed ID: 20870033
    [TBL] [Abstract][Full Text] [Related]  

  • 9. MetaMap Lite: an evaluation of a new Java implementation of MetaMap.
    Demner-Fushman D; Rogers WJ; Aronson AR
    J Am Med Inform Assoc; 2017 Jul; 24(4):841-844. PubMed ID: 28130331
    [TBL] [Abstract][Full Text] [Related]  

  • 10. [A customized method for information extraction from unstructured text data in the electronic medical records].
    Bao XY; Huang WJ; Zhang K; Jin M; Li Y; Niu CZ
    Beijing Da Xue Xue Bao Yi Xue Ban; 2018 Apr; 50(2):256-263. PubMed ID: 29643524
    [TBL] [Abstract][Full Text] [Related]  

  • 11. The 2019 National Natural language processing (NLP) Clinical Challenges (n2c2)/Open Health NLP (OHNLP) shared task on clinical concept normalization for clinical records.
    Henry S; Wang Y; Shen F; Uzuner O
    J Am Med Inform Assoc; 2020 Oct; 27(10):1529-1537. PubMed ID: 32968800
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Facilitating clinical research through automation: Combining optical character recognition with natural language processing.
    Hom J; Nikowitz J; Ottesen R; Niland JC
    Clin Trials; 2022 Oct; 19(5):504-511. PubMed ID: 35608136
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Using Medical Text Extraction, Reasoning and Mapping System (MTERMS) to process medication information in outpatient clinical notes.
    Zhou L; Plasek JM; Mahoney LM; Karipineni N; Chang F; Yan X; Chang F; Dimaggio D; Goldman DS; Rocha RA
    AMIA Annu Symp Proc; 2011; 2011():1639-48. PubMed ID: 22195230
    [TBL] [Abstract][Full Text] [Related]  

  • 14. SemEHR: A general-purpose semantic search system to surface semantic data from clinical notes for tailored care, trial recruitment, and clinical research.
    Wu H; Toti G; Morley KI; Ibrahim ZM; Folarin A; Jackson R; Kartoglu I; Agrawal A; Stringer C; Gale D; Gorrell G; Roberts A; Broadbent M; Stewart R; Dobson RJB
    J Am Med Inform Assoc; 2018 May; 25(5):530-537. PubMed ID: 29361077
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Comparison of MetaMap and cTAKES for entity extraction in clinical notes.
    Reátegui R; Ratté S
    BMC Med Inform Decis Mak; 2018 Sep; 18(Suppl 3):74. PubMed ID: 30255810
    [TBL] [Abstract][Full Text] [Related]  

  • 16. MLM-based typographical error correction of unstructured medical texts for named entity recognition.
    Lee EB; Heo GE; Choi CM; Song M
    BMC Bioinformatics; 2022 Nov; 23(1):486. PubMed ID: 36384464
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Task definition, annotated dataset, and supervised natural language processing models for symptom extraction from unstructured clinical notes.
    Steinkamp JM; Bala W; Sharma A; Kantrowitz JJ
    J Biomed Inform; 2020 Feb; 102():103354. PubMed ID: 31838210
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Extraction of UMLS® Concepts Using Apache cTAKES™ for German Language.
    Becker M; Böckmann B
    Stud Health Technol Inform; 2016; 223():71-6. PubMed ID: 27139387
    [TBL] [Abstract][Full Text] [Related]  

  • 19. The interaction of domain knowledge and linguistic structure in natural language processing: interpreting hypernymic propositions in biomedical text.
    Rindflesch TC; Fiszman M
    J Biomed Inform; 2003 Dec; 36(6):462-77. PubMed ID: 14759819
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Automated SNOMED CT concept and attribute relationship detection through a web-based implementation of cTAKES.
    Kersloot MG; Lau F; Abu-Hanna A; Arts DL; Cornet R
    J Biomed Semantics; 2019 Sep; 10(1):14. PubMed ID: 31533810
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 45.