BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

136 related articles for article (PubMed ID: 17947619)

  • 1. Identifying smokers with a medical extraction system.
    Clark C; Good K; Jezierny L; Macpherson M; Wilson B; Chajewska U
    J Am Med Inform Assoc; 2008; 15(1):36-9. PubMed ID: 17947619
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Mayo clinic NLP system for patient smoking status identification.
    Savova GK; Ogren PV; Duffy PH; Buntrock JD; Chute CG
    J Am Med Inform Assoc; 2008; 15(1):25-8. PubMed ID: 17947622
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Use of semantic features to classify patient smoking status.
    McCormick PJ; Elhadad N; Stetson PD
    AMIA Annu Symp Proc; 2008 Nov; 2008():450-4. PubMed ID: 18998969
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Identifying patient smoking status from medical discharge records.
    Uzuner O; Goldstein I; Luo Y; Kohane I
    J Am Med Inform Assoc; 2008; 15(1):14-24. PubMed ID: 17947624
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Five-way smoking status classification using text hot-spot identification and error-correcting output codes.
    Cohen AM
    J Am Med Inform Assoc; 2008; 15(1):32-5. PubMed ID: 17947623
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Natural language processing and machine learning to enable automatic extraction and classification of patients' smoking status from electronic medical records.
    Caccamisi A; Jørgensen L; Dalianis H; Rosenlund M
    Ups J Med Sci; 2020 Nov; 125(4):316-324. PubMed ID: 32696698
    [TBL] [Abstract][Full Text] [Related]  

  • 7. A hybrid approach to determining modification of clinical diagnoses.
    Pakhomov S; Chute CG
    AMIA Annu Symp Proc; 2006; 2006():609-13. PubMed ID: 17238413
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Identifying Mentions of Pain in Mental Health Records Text: A Natural Language Processing Approach.
    Chaturvedi J; Velupillai S; Stewart R; Roberts A
    Stud Health Technol Inform; 2024 Jan; 310():695-699. PubMed ID: 38269898
    [TBL] [Abstract][Full Text] [Related]  

  • 9. PDF text classification to leverage information extraction from publication reports.
    Bui DD; Del Fiol G; Jonnalagadda S
    J Biomed Inform; 2016 Jun; 61():141-8. PubMed ID: 27044929
    [TBL] [Abstract][Full Text] [Related]  

  • 10. 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]  

  • 11. Medical i2b2 NLP smoking challenge: the A-Life system architecture and methodology.
    Heinze DT; Morsch ML; Potter BC; Sheffer RE
    J Am Med Inform Assoc; 2008; 15(1):40-3. PubMed ID: 17947621
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Classification techniques with minimal labelling effort and application to medical reports.
    Saad FH; Bell GD; de la Iglesia B
    Int J Data Min Bioinform; 2008; 2(3):268-87. PubMed ID: 19024498
    [TBL] [Abstract][Full Text] [Related]  

  • 13. 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]  

  • 14. Mayo clinic smoking status classification system: extensions and improvements.
    Sohn S; Savova GK
    AMIA Annu Symp Proc; 2009 Nov; 2009():619-23. PubMed ID: 20351929
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Trie-based rule processing for clinical NLP: A use-case study of n-trie, making the ConText algorithm more efficient and scalable.
    Shi J; Hurdle JF
    J Biomed Inform; 2018 Sep; 85():106-113. PubMed ID: 30092358
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Identifying and extracting patient smoking status information from clinical narrative texts in Spanish.
    Figueroa RL; Soto DA; Pino EJ
    Annu Int Conf IEEE Eng Med Biol Soc; 2014; 2014():2710-3. PubMed ID: 25570550
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Natural language processing to identify adverse drug events.
    Gysbers M; Reichley R; Kilbridge PM; Noirot L; Nagarajan R; Dunagan WC; Bailey TC
    AMIA Annu Symp Proc; 2008 Nov; ():961. PubMed ID: 18999130
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Mining fall-related information in clinical notes: Comparison of rule-based and novel word embedding-based machine learning approaches.
    Topaz M; Murga L; Gaddis KM; McDonald MV; Bar-Bachar O; Goldberg Y; Bowles KH
    J Biomed Inform; 2019 Feb; 90():103103. PubMed ID: 30639392
    [TBL] [Abstract][Full Text] [Related]  

  • 19. 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]  

  • 20. Development and evaluation of RapTAT: a machine learning system for concept mapping of phrases from medical narratives.
    Gobbel GT; Reeves R; Jayaramaraja S; Giuse D; Speroff T; Brown SH; Elkin PL; Matheny ME
    J Biomed Inform; 2014 Apr; 48():54-65. PubMed ID: 24316051
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.