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

Pharmacovigilance (134) Infodemiology and Infoveillance (1349) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1641) Natural Language Processing (692) Adverse Drug Events Detection, Pharmacovigilance and Surveillance (156) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1041)

Published on in Vol 5, No 2 (2019): Apr-Jun

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/11264, first published .
Early Detection of Adverse Drug Reactions in Social Health Networks: A Natural Language Processing Pipeline for Signal Detection

Early Detection of Adverse Drug Reactions in Social Health Networks: A Natural Language Processing Pipeline for Signal Detection

Early Detection of Adverse Drug Reactions in Social Health Networks: A Natural Language Processing Pipeline for Signal Detection

Authors of this article:

Azadeh Nikfarjam1 Author Orcid Image ;   Julia D Ransohoff1 Author Orcid Image ;   Alison Callahan1 Author Orcid Image ;   Erik Jones2 Author Orcid Image ;   Brian Loew2 Author Orcid Image ;   Bernice Y Kwong3 Author Orcid Image ;   Kavita Y Sarin3 Author Orcid Image ;   Nigam H Shah1 Author Orcid Image
Article Authors Cited by (23) Tweetations (10) Metrics

Journals

  1. Zhou Z, Hultgren K. Complementing the US Food and Drug Administration Adverse Event Reporting System With Adverse Drug Reaction Reporting From Social Media: Comparative Analysis. JMIR Public Health and Surveillance 2020;6(3):e19266 View
  2. Audeh B, Bellet F, Beyens M, Lillo-Le Louët A, Bousquet C. Use of Social Media for Pharmacovigilance Activities: Key Findings and Recommendations from the Vigi4Med Project. Drug Safety 2020;43(9):835 View
  3. Li X, Lin X, Ren H, Guo J. Ontological Organization and Bioinformatic Analysis of Adverse Drug Reactions From Package Inserts: Development and Usability Study. Journal of Medical Internet Research 2020;22(7):e20443 View
  4. Eicher T, Kinnebrew G, Patt A, Spencer K, Ying K, Ma Q, Machiraju R, Mathé E. Metabolomics and Multi-Omics Integration: A Survey of Computational Methods and Resources. Metabolites 2020;10(5):202 View
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  6. Leis A, Ronzano F, Mayer M, Furlong L, Sanz F. Evaluating Behavioral and Linguistic Changes During Drug Treatment for Depression Using Tweets in Spanish: Pairwise Comparison Study. Journal of Medical Internet Research 2020;22(12):e20920 View
  7. Golder S, Smith K, O’Connor K, Gross R, Hennessy S, Gonzalez-Hernandez G. A Comparative View of Reported Adverse Effects of Statins in Social Media, Regulatory Data, Drug Information Databases and Systematic Reviews. Drug Safety 2021;44(2):167 View
  8. Shin H, Cha J, Lee C, Song H, Jeong H, Kim J, Lee S. The 2011–2020 Trends of Data-Driven Approaches in Medical Informatics for Active Pharmacovigilance. Applied Sciences 2021;11(5):2249 View
  9. Bates D, Williams E. Quality and Safety: Learning from the Past and (Re)Imagining the Future. The Journal of Allergy and Clinical Immunology: In Practice 2022;10(12):3141 View
  10. Barrutia L, Vega-Gutiérrez J, Santamarina-Albertos A. Benefits, drawbacks, and challenges of social media use in dermatology: a systematic review. Journal of Dermatological Treatment 2022;33(6):2738 View
  11. Dang A. Real-World Evidence: A Primer. Pharmaceutical Medicine 2023;37(1):25 View
  12. Kaas‐Hansen B, Placido D, Rodríguez C, Thorsen‐Meyer H, Gentile S, Nielsen A, Brunak S, Jürgens G, Andersen S. Language‐agnostic pharmacovigilant text mining to elicit side effects from clinical notes and hospital medication records. Basic & Clinical Pharmacology & Toxicology 2022;131(4):282 View
  13. Cummins J, Nambudiri V. Natural language processing: A window to understanding skincare trends. International Journal of Medical Informatics 2022;160:104705 View
  14. Noh Y, Ko H, Kim J, Yoon D, Choe Y, Choe S, Jung J, Shin J. Barriers to COVID-19 vaccine surveillance: the issue of under-reporting adverse events. Epidemiology and Health 2023;45:e2023054 View
  15. Botsis T, Kreimeyer K. Improving drug safety with adverse event detection using natural language processing. Expert Opinion on Drug Safety 2023;22(8):659 View
  16. Golder S, O'Connor K, Wang Y, Klein A, Gonzalez Hernandez G. The Value of Social Media Analysis for Adverse Events Detection and Pharmacovigilance: Scoping Review. JMIR Public Health and Surveillance 2024;10:e59167 View
  17. Karapetiantz P, Audeh B, Redjdal A, Tiffet T, Bousquet C, Jaulent M. Monitoring Adverse Drug Events in Web Forums: Evaluation of a Pipeline and Use Case Study. Journal of Medical Internet Research 2024;26:e46176 View
  18. Morris R, Ali R, Cheng F. Drug Repurposing Using FDA Adverse Event Reporting System (FAERS) Database. Current Drug Targets 2024;25(7):454 View
  19. Naderian S, Rahmani R, Samad-Soltani T. A Natural Language Processing Framework for Detecting Adverse Drug Reactions in Clinical Structured Drug Reviews. International Journal of Drug Research in Clinics 2024;2:e9 View

Books/Policy Documents

  1. Lobantsev A, Loginova V, Burlakova Y, Andreev N, Matveeva V, Filimonova I, Dobrenko N, Gusarova N. Digital Transformation and Global Society. View
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