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

Pharmacovigilance (134) Reviews on Public Health Technology and Innovation (69) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1041) Infodemiology and Infoveillance (1349) Mass Media/Social Media Communication and Campaigns (461)

Published on in Vol 7, No 6 (2021): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/30137, first published .
The Use of Social Media in Detecting Drug Safety–Related New Black Box Warnings, Labeling Changes, or Withdrawals: Scoping Review

The Use of Social Media in Detecting Drug Safety–Related New Black Box Warnings, Labeling Changes, or Withdrawals: Scoping Review

The Use of Social Media in Detecting Drug Safety–Related New Black Box Warnings, Labeling Changes, or Withdrawals: Scoping Review

Authors of this article:

Jae-Young Lee1 Author Orcid Image ;   Yae-Seul Lee2 Author Orcid Image ;   Dong Hyun Kim1 Author Orcid Image ;   Han Sol Lee1 Author Orcid Image ;   Bo Ram Yang1 Author Orcid Image ;   Myeong Gyu Kim2, 3 Author Orcid Image
Article Authors Cited by (22) Tweetations (4) Metrics

Journals

  1. Carpenter K, Altman R. Using GPT-3 to Build a Lexicon of Drugs of Abuse Synonyms for Social Media Pharmacovigilance. Biomolecules 2023;13(2):387 View
  2. Kim M, Kim M, Kim J, Kim K. Fine-Tuning BERT Models to Classify Misinformation on Garlic and COVID-19 on Twitter. International Journal of Environmental Research and Public Health 2022;19(9):5126 View
  3. Salas M, Petracek J, Yalamanchili P, Aimer O, Kasthuril D, Dhingra S, Junaid T, Bostic T. The Use of Artificial Intelligence in Pharmacovigilance: A Systematic Review of the Literature. Pharmaceutical Medicine 2022;36(5):295 View
  4. Nishioka S, Watanabe T, Asano M, Yamamoto T, Kawakami K, Yada S, Aramaki E, Yajima H, Kizaki H, Hori S, Yang J. Identification of hand-foot syndrome from cancer patients’ blog posts: BERT-based deep-learning approach to detect potential adverse drug reaction symptoms. PLOS ONE 2022;17(5):e0267901 View
  5. Goyer C, Castillon G, Moride Y. Implementation of Interventions and Policies on Opioids and Awareness of Opioid-Related Harms in Canada: A Multistage Mixed Methods Descriptive Study. International Journal of Environmental Research and Public Health 2022;19(9):5122 View
  6. Powell G, Kara V, Painter J, Schifano L, Merico E, Bate A. Engaging Patients via Online Healthcare Fora: Three Pharmacovigilance Use Cases. Frontiers in Pharmacology 2022;13 View
  7. Soboleva M, Loskutova E, Kosova I. Pharmacoepidemiological study of the use of e-pharmacies by the population. Journal Of Advanced Pharmacy Education And Research 2022;12(3):36 View
  8. Back H, Choi S, Kim M. Adverse Events of GLP-1 Receptor Agonists for Weight Loss: Twitter and a National Pharmacovigilance Database. Drug Targets and Therapeutics 2023;2(1):41 View
  9. Golder S, O'Connor K, Wang Y, Gonzalez Hernandez G. The Role of Social Media for Identifying Adverse Drug Events Data in Pharmacovigilance: Protocol for a Scoping Review. JMIR Research Protocols 2023;12:e47068 View
  10. Nishioka S, Asano M, Yada S, Aramaki E, Yajima H, Yanagisawa Y, Sayama K, Kizaki H, Hori S. Adverse event signal extraction from cancer patients’ narratives focusing on impact on their daily-life activities. Scientific Reports 2023;13(1) View
  11. 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
  12. Zolnour A, Eldredge C, Faiola A, Yaghoobzadeh Y, Khani M, Foy D, Topaz M, Kharrazi H, Fung K, Fontelo P, Davoudi A, Tabaie A, Breitinger S, Oesterle T, Rouhizadeh M, Zonnor Z, Moen H, Patrick T, Zolnoori M. A risk identification model for detection of patients at risk of antidepressant discontinuation. Frontiers in Artificial Intelligence 2023;6 View
  13. Menang O, Kuemmerle A, Maigetter K, Burri C. Strategies and interventions to strengthen pharmacovigilance systems in low-income and middle-income countries: a scoping review. BMJ Open 2023;13(9):e071079 View
  14. Hauben M. The Utility of a Social Listening Program to Support Safety Surveillance of Tozinameran (COVID-19 Vaccine)-a Brief Survey of Pharmacovigilance Professionals. Clinical Therapeutics 2024;46(2):173 View
  15. Dong F, Guo W, Liu J, Patterson T, Hong H. BERT-based language model for accurate drug adverse event extraction from social media: implementation, evaluation, and contributions to pharmacovigilance practices. Frontiers in Public Health 2024;12 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. Hauben M. A Pharmacovigilance Florilegium. Clinical Therapeutics 2024;46(7):520 View
  18. Kim J, Davis S, Matheny M, Smith J. Integrating electronic health records with other data sources for postmarket drug safety signal identification: a review. Frontiers in Drug Safety and Regulation 2024;4 View

Books/Policy Documents

  1. Joshi-Barr S, Wampole M. Drug Discovery and Evaluation: Safety and Pharmacokinetic Assays. View
  2. Imbrici P, De Bellis M, Liantonio A, De Luca A. Computational Toxicology. View
  3. Joshi-Barr S, Wampole M. Drug Discovery and Evaluation: Safety and Pharmacokinetic Assays. View