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Citing this Article

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Published on 17.05.11 in Vol 13, No 2 (2011): Apr-Jun

This paper is in the following e-collection/theme issue:

Works citing "Computer-Assisted Update of a Consumer Health Vocabulary Through Mining of Social Network Data"

Kristina M Doing-Harris, Qing Zeng-Treitler

J Med Internet Res 2011 (May 17); 13(2):e37 

According to Crossref, the following articles are citing this article (DOI 10.2196/jmir.1636):

(note that this is only a small subset of citations)

  1. Taylor J, Pagliari C. Mining social media data: How are research sponsors and researchers addressing the ethical challenges?. Research Ethics 2018;14(2):1
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  2. Adamusiak T, Shimoyama N, Shimoyama M. Next Generation Phenotyping Using the Unified Medical Language System. JMIR Medical Informatics 2014;2(1):e5
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  3. Chen AT, Carriere RM, Kaplan SJ. The User Knows What to Call It: Incorporating Patient Voice Through User-Contributed Tags on a Participatory Platform About Health Management. Journal of Medical Internet Research 2017;19(9):e292
    CrossRef
  4. Moorhead SA, Hazlett DE, Harrison L, Carroll JK, Irwin A, Hoving C. A New Dimension of Health Care: Systematic Review of the Uses, Benefits, and Limitations of Social Media for Health Communication. Journal of Medical Internet Research 2013;15(4):e85
    CrossRef
  5. Park MS, He Z, Chen Z, Oh S, Bian J. Consumers’ Use of UMLS Concepts on Social Media: Diabetes-Related Textual Data Analysis in Blog and Social Q&A Sites. JMIR Medical Informatics 2016;4(4):e41
    CrossRef
  6. Chen J, Jagannatha AN, Fodeh SJ, Yu H. Ranking Medical Terms to Support Expansion of Lay Language Resources for Patient Comprehension of Electronic Health Record Notes: Adapted Distant Supervision Approach. JMIR Medical Informatics 2017;5(4):e42
    CrossRef
  7. Wu DTY, Xin C, Bindhu S, Xu C, Sachdeva J, Brown JL, Jung H. Clinician Perspectives and Design Implications in Using Patient-Generated Health Data to Improve Mental Health Practices: Mixed Methods Study. JMIR Formative Research 2020;4(8):e18123
    CrossRef
  8. Lin Y, He Y. The ontology of genetic susceptibility factors (OGSF) and its application in modeling genetic susceptibility to vaccine adverse events. Journal of Biomedical Semantics 2014;5(1):19
    CrossRef
  9. Scotch M, Baarson B, Beard R, Lauder R, Varman A, Halden RU. Examining the Differences in Format and Characteristics of Zoonotic Virus Surveillance Data on State Agency Websites. Journal of Medical Internet Research 2013;15(4):e90
    CrossRef
  10. Gu G, Zhang X, Zhu X, Jian Z, Chen K, Wen D, Gao L, Zhang S, Wang F, Ma H, Lei J. Development of a Consumer Health Vocabulary by Mining Health Forum Texts Based on Word Embedding: Semiautomatic Approach. JMIR Medical Informatics 2019;7(2):e12704
    CrossRef
  11. MacLean DL, Heer J. Identifying medical terms in patient-authored text: a crowdsourcing-based approach. Journal of the American Medical Informatics Association 2013;20(6):1120
    CrossRef
  12. Chen C, Huang E, Yan H. Detecting the association of health problems in consumer-level medical text. Journal of Information Science 2018;44(1):3
    CrossRef
  13. He Z, Chen Z, Oh S, Hou J, Bian J. Enriching consumer health vocabulary through mining a social Q&A site: A similarity-based approach. Journal of Biomedical Informatics 2017;69:75
    CrossRef
  14. Ping X, Chung Y, Tseng Y, Liang J, Yang P, Huang G, Lai F. A Web-Based Data-Querying Tool Based on Ontology-Driven Methodology and Flowchart-Based Model. JMIR Medical Informatics 2013;1(1):e2
    CrossRef
  15. Wicks P, Sulham KA, Gnanasakthy A. Quality of Life in Organ Transplant Recipients Participating in an Online Transplant Community. The Patient - Patient-Centered Outcomes Research 2014;7(1):73
    CrossRef
  16. Hoang T, Liu J, Pratt N, Zheng VW, Chang KC, Roughead E, Li J. Authenticity and credibility aware detection of adverse drug events from social media. International Journal of Medical Informatics 2018;120:101
    CrossRef
  17. Lu Y, Wu Y, Liu J, Li J, Zhang P. Understanding Health Care Social Media Use From Different Stakeholder Perspectives: A Content Analysis of an Online Health Community. Journal of Medical Internet Research 2017;19(4):e109
    CrossRef
  18. Konstantinidis S, Fernandez-Luque L, Bamidis P, Karlsen R. The Role of Taxonomies in Social Media and the Semantic Web for Health Education. Methods of Information in Medicine 2013;52(02):168
    CrossRef
  19. Kaplan SJ, Chen AT, Carriere RM. De‐constructing the co‐construction: Researcher stance, the nature of data and community building in an online participatory platform to create a knowledge repository. Proceedings of the Association for Information Science and Technology 2017;54(1):203
    CrossRef
  20. Robillard JM, Whiteley L, Johnson TW, Lim J, Wasserman WW, Illes J. Utilizing Social Media to Study Information-Seeking and Ethical Issues in Gene Therapy. Journal of Medical Internet Research 2013;15(3):e44
    CrossRef
  21. Hartzler AL, Taylor MN, Park A, Griffiths T, Backonja U, McDonald DW, Wahbeh S, Brown C, Pratt W. Leveraging cues from person-generated health data for peer matching in online communities. Journal of the American Medical Informatics Association 2016;23(3):496
    CrossRef
  22. Bäumer FS, Dollmann M, Geierhos M. Find a Physician by Matching Medical Needs Described in your Own Words. Procedia Computer Science 2015;63:417
    CrossRef
  23. Hoang T, Liu J, Pratt N, Zheng VW, Chang KC, Roughead E, Li J. Authenticity and credibility aware detection of adverse drug events from social media. International Journal of Medical Informatics 2018;120:157
    CrossRef
  24. Dreisbach C, Koleck TA, Bourne PE, Bakken S. A systematic review of natural language processing and text mining of symptoms from electronic patient-authored text data. International Journal of Medical Informatics 2019;125:37
    CrossRef
  25. Tapi Nzali MD, Aze J, Bringay S, Lavergne C, Mollevi C, Optiz T. Reconciliation of patient/doctor vocabulary in a structured resource. Health Informatics Journal 2019;25(4):1219
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  26. Pierce CE, Bouri K, Pamer C, Proestel S, Rodriguez HW, Van Le H, Freifeld CC, Brownstein JS, Walderhaug M, Edwards IR, Dasgupta N. Evaluation of Facebook and Twitter Monitoring to Detect Safety Signals for Medical Products: An Analysis of Recent FDA Safety Alerts. Drug Safety 2017;40(4):317
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  27. Sokolova M, El Emam K, Arbuckle L, Neri E, Rose S, Jonker E. P2P Watch: Personal Health Information Detection in Peer-to-Peer File-Sharing Networks. Journal of Medical Internet Research 2012;14(4):e95
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  28. Chen AT, Carriere R, Kaplan SJ, Colht K, Morey OT, Flaherty MG, Moser GB, Slager SL, Price C. Exploring collective tagging as a mechanism to elicit language about health management. Proceedings of the Association for Information Science and Technology 2016;53(1):1
    CrossRef
  29. de Lusignan S, Liyanage H, McGagh D, Jani BD, Bauwens J, Byford R, Evans D, Fahey T, Greenhalgh T, Jones N, Mair FS, Okusi C, Parimalanathan V, Pell JP, Sherlock J, Tamburis O, Tripathy M, Ferreira F, Williams J, Hobbs FDR. COVID-19 Surveillance in a Primary Care Sentinel Network: In-Pandemic Development of an Application Ontology. JMIR Public Health and Surveillance 2020;6(4):e21434
    CrossRef
  30. Alasmari A, Zhou L. Share to Seek: The Effects of Disease Complexity on Health Information–Seeking Behavior. Journal of Medical Internet Research 2021;23(3):e21642
    CrossRef
  31. Monselise M, Greenberg J, Liang OS, Pascua S, Kim H, Kelly M, Boone JP, Yang CC. An Automatic Approach to Extending the Consumer Health Vocabulary. Journal of Data and Information Science 2021;6(1):35
    CrossRef
  32. Ibrahim M, Gauch S, Salman O, Alqahtani M. An automated method to enrich consumer health vocabularies using GloVe word embeddings and an auxiliary lexical resource. PeerJ Computer Science 2021;7:e668
    CrossRef
  33. Ondov B, Attal K, Demner-Fushman D. A survey of automated methods for biomedical text simplification. Journal of the American Medical Informatics Association 2022;29(11):1976
    CrossRef
  34. Tong C, Margolin D, Chunara R, Niederdeppe J, Taylor T, Dunbar N, King AJ. Search Term Identification Methods for Computational Health Communication: Word Embedding and Network Approach for Health Content on YouTube. JMIR Medical Informatics 2022;10(8):e37862
    CrossRef
  35. Roche V, Robert J, Salam H. A holistic AI-based approach for pharmacovigilance optimization from patients behavior on social media. Artificial Intelligence in Medicine 2023;144:102638
    CrossRef
  36. Tenorio JM, de Moraes FL, Pisa IT. CHV.br: Exploratory study for the development of a consumer health vocabulary (CHV) supported by a network model for Brazilian Portuguese language. Journal of Information Science 2023;
    CrossRef

According to Crossref, the following books are citing this article (DOI 10.2196/jmir.1636):

  1. Jiang L, Yang CC. Social Computing, Behavioral-Cultural Modeling, and Prediction. 2015. Chapter 36:314
    CrossRef
  2. . Social Web and Health Research. 2019. Chapter 6:103
    CrossRef
  3. Mayer M, Fernández-Luque L, Leis A. Participatory Health Through Social Media. 2016. :67
    CrossRef
  4. Myneni S, Fujimoto K, Cohen T. Cognitive Informatics in Health and Biomedicine. 2017. Chapter 15:315
    CrossRef
  5. . Relevance Ranking for Vertical Search Engines. 2014. :201
    CrossRef
  6. Santini M, Jönsson A, Strandqvist W, Cederblad G, Nyström M, Alirezaie M, Lind L, Blomqvist E, Lindén M, Kristoffersson A. Cyber-Physical Systems for Social Applications. 2019. chapter 6:98
    CrossRef
  7. Ozbolt J, Bakken S, Dykes PC. Biomedical Informatics. 2014. Chapter 15:475
    CrossRef
  8. Bakken S, Dykes PC, Rossetti SC, Ozbolt JG. Biomedical Informatics. 2021. Chapter 17:575
    CrossRef