Published on in Vol 17, No 7 (2015): July

Adverse Drug Reaction Identification and Extraction in Social Media: A Scoping Review

Adverse Drug Reaction Identification and Extraction in Social Media: A Scoping Review

Adverse Drug Reaction Identification and Extraction in Social Media: A Scoping Review

Journals

  1. 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
  2. Karapetiantz P, Bellet F, Audeh B, Lardon J, Leprovost D, Aboukhamis R, Morlane-Hondère F, Grouin C, Burgun A, Katsahian S, Jaulent M, Beyens M, Lillo-Le Louët A, Bousquet C. Descriptions of Adverse Drug Reactions Are Less Informative in Forums Than in the French Pharmacovigilance Database but Provide More Unexpected Reactions. Frontiers in Pharmacology 2018;9 View
  3. Pierce C, Bouri K, Pamer C, Proestel S, Rodriguez H, Van Le H, Freifeld C, Brownstein J, Walderhaug M, Edwards I, 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 View
  4. Convertino I, Ferraro S, Blandizzi C, Tuccori M. The usefulness of listening social media for pharmacovigilance purposes: a systematic review. Expert Opinion on Drug Safety 2018;17(11):1081 View
  5. Hughes S, Lacasse J, Spaulding-Givens J. The micro-to-macro realities of antidepressant taking: Users’ experiences in the context of contested science and industry promotion. Qualitative Social Work 2020;19(5-6):1219 View
  6. Alimova I, Tutubalina E. Entity-Level Classification of Adverse Drug Reaction: A Comparative Analysis of Neural Network Models. Programming and Computer Software 2019;45(8):439 View
  7. Wang W, Cheung B, Leung Z, Chan K, See-To E. A Social Media Mining and Analysis Approach for Supporting Cyber Youth Work. International Journal of Knowledge and Systems Science 2017;8(2):1 View
  8. Kheloufi F, Default A, Blin O, Micallef J. Investigating patient narratives posted on Internet and their informativeness level for pharmacovigilance purpose: The example of comments about statins. Therapies 2017;72(4):483 View
  9. Raghupathi V, Zhou Y, Raghupathi W. Exploring Big Data Analytic Approaches to Cancer Blog Text Analysis. International Journal of Healthcare Information Systems and Informatics 2019;14(4):1 View
  10. Pappa D, Stergioulas L. Harnessing social media data for pharmacovigilance: a review of current state of the art, challenges and future directions. International Journal of Data Science and Analytics 2019;8(2):113 View
  11. Tutubalina E, Miftahutdinov Z, Nugmanov R, Madzhidov T, Nikolenko S, Alimova I, Tropsha A. Using semantic analysis of texts for the identification of drugs with similar therapeutic effects. Russian Chemical Bulletin 2017;66(11):2180 View
  12. Gachloo M, Wang Y, Xia J. A review of drug knowledge discovery using BioNLP and tensor or matrix decomposition. Genomics & Informatics 2019;17(2):e18 View
  13. Zhou L, Zhang D, Yang C, Wang Y. Harnessing social media for health information management. Electronic Commerce Research and Applications 2018;27:139 View
  14. Krallinger M, Rabal O, Lourenço A, Oyarzabal J, Valencia A. Information Retrieval and Text Mining Technologies for Chemistry. Chemical Reviews 2017;117(12):7673 View
  15. Safarnejad L, Xu Q, Ge Y, Bagavathi A, Krishnan S, Chen S. Identifying Influential Factors in the Discussion Dynamics of Emerging Health Issues on Social Media: Computational Study. JMIR Public Health and Surveillance 2020;6(3):e17175 View
  16. Abdellaoui R, Schück S, Texier N, Burgun A. Filtering Entities to Optimize Identification of Adverse Drug Reaction From Social Media: How Can the Number of Words Between Entities in the Messages Help?. JMIR Public Health and Surveillance 2017;3(2):e36 View
  17. Abdellaoui R, Foulquié P, Texier N, Faviez C, Burgun A, Schück S. Detection of Cases of Noncompliance to Drug Treatment in Patient Forum Posts: Topic Model Approach. Journal of Medical Internet Research 2018;20(3):e85 View
  18. Liu Y, Shi J, Chen Y. Patient-centered and experience-aware mining for effective adverse drug reaction discovery in online health forums. Journal of the Association for Information Science and Technology 2018;69(2):215 View
  19. Kalf R, Makady A, ten Ham R, Meijboom K, Goettsch W. Use of Social Media in the Assessment of Relative Effectiveness: Explorative Review With Examples From Oncology. JMIR Cancer 2018;4(1):e11 View
  20. Powell G, Seifert H, Reblin T, Burstein P, Blowers J, Menius J, Painter J, Thomas M, Pierce C, Rodriguez H, Brownstein J, Freifeld C, Bell H, Dasgupta N. Social Media Listening for Routine Post-Marketing Safety Surveillance. Drug Safety 2016;39(5):443 View
  21. Correia R, Wood I, Bollen J, Rocha L. Mining Social Media Data for Biomedical Signals and Health-Related Behavior. Annual Review of Biomedical Data Science 2020;3(1):433 View
  22. Sinnenberg L, Buttenheim A, Padrez K, Mancheno C, Ungar L, Merchant R. Twitter as a Tool for Health Research: A Systematic Review. American Journal of Public Health 2017;107(1):e1 View
  23. Audeh B, Beigbeder M, Zimmermann A, Jaillon P, Bousquet C, Choo K. Vigi4Med Scraper: A Framework for Web Forum Structured Data Extraction and Semantic Representation. PLOS ONE 2017;12(1):e0169658 View
  24. Bousquet C, Dahamna B, Guillemin-Lanne S, Darmoni S, Faviez C, Huot C, Katsahian S, Leroux V, Pereira S, Richard C, Schück S, Souvignet J, Lillo-Le Louët A, Texier N. The Adverse Drug Reactions from Patient Reports in Social Media Project: Five Major Challenges to Overcome to Operationalize Analysis and Efficiently Support Pharmacovigilance Process. JMIR Research Protocols 2017;6(9):e179 View
  25. Li F, Liu W, Yu H. Extraction of Information Related to Adverse Drug Events from Electronic Health Record Notes: Design of an End-to-End Model Based on Deep Learning. JMIR Medical Informatics 2018;6(4):e12159 View
  26. Chen X, Faviez C, Schuck S, Lillo-Le-Louët A, Texier N, Dahamna B, Huot C, Foulquié P, Pereira S, Leroux V, Karapetiantz P, Guenegou-Arnoux A, Katsahian S, Bousquet C, Burgun A. Mining Patients' Narratives in Social Media for Pharmacovigilance: Adverse Effects and Misuse of Methylphenidate. Frontiers in Pharmacology 2018;9 View
  27. Dai H, Touray M, Jonnagaddala J, Syed-Abdul S. Feature Engineering for Recognizing Adverse Drug Reactions from Twitter Posts. Information 2016;7(2):27 View
  28. Abbasi A, Li J, Abbasi S, Adjeroh D, Abate M, Zheng W. Don't Mention It? Analyzing User-Generated Content Signals for Early Adverse Drug Event Warnings. SSRN Electronic Journal 2015 View
  29. Lardon J, Bellet F, Aboukhamis R, Asfari H, Souvignet J, Jaulent M, Beyens M, Lillo-LeLouët A, Bousquet C. Evaluating Twitter as a complementary data source for pharmacovigilance. Expert Opinion on Drug Safety 2018;17(8):763 View
  30. Karapetiantz P, Lillo-Le Louët A, Bousquet C. Informativité des forums de discussion français pour l’évaluation des effets indésirables du baclofène. Therapies 2019;74(6):569 View
  31. Jagannatha A, Liu F, Liu W, Yu H. Overview of the First Natural Language Processing Challenge for Extracting Medication, Indication, and Adverse Drug Events from Electronic Health Record Notes (MADE 1.0). Drug Safety 2019;42(1):99 View
  32. 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
  33. Bravo À, Li T, Su A, Good B, Furlong L. Combining machine learning, crowdsourcing and expert knowledge to detect chemical-induced diseases in text. Database 2016;2016:baw094 View
  34. Sinha M, Freifeld C, Brownstein J, Donneyong M, Rausch P, Lappin B, Zhou E, Dal Pan G, Pawar A, Hwang T, Avorn J, Kesselheim A. Social Media Impact of the Food and Drug Administration's Drug Safety Communication Messaging About Zolpidem: Mixed-Methods Analysis. JMIR Public Health and Surveillance 2018;4(1):e1 View
  35. Munkhdalai T, Liu F, Yu H. Clinical Relation Extraction Toward Drug Safety Surveillance Using Electronic Health Record Narratives: Classical Learning Versus Deep Learning. JMIR Public Health and Surveillance 2018;4(2):e29 View
  36. Abbasi A, Li J, Adjeroh D, Abate M, Zheng W. Don’t Mention It? Analyzing User-Generated Content Signals for Early Adverse Event Warnings. Information Systems Research 2019;30(3):1007 View
  37. Sutphin C, Lee K, Yepes A, Uzuner Ö, McInnes B. Adverse drug event detection using reason assignments in FDA drug labels. Journal of Biomedical Informatics 2020;110:103552 View
  38. Topaz M, Lai K, Dhopeshwarkar N, Seger D, Sa’adon R, Goss F, Rozenblum R, Zhou L. Clinicians’ Reports in Electronic Health Records Versus Patients’ Concerns in Social Media: A Pilot Study of Adverse Drug Reactions of Aspirin and Atorvastatin. Drug Safety 2016;39(3):241 View
  39. Dolley S. Big Data’s Role in Precision Public Health. Frontiers in Public Health 2018;6 View
  40. Bhattacharya M, Snyder S, Malin M, Truffa M, Marinic S, Engelmann R, Raheja R. Using Social Media Data in Routine Pharmacovigilance: A Pilot Study to Identify Safety Signals and Patient Perspectives. Pharmaceutical Medicine 2017;31(3):167 View
  41. Turner J, Kowey P, Rodriguez I, Cabell C, Gintant G, Green C, Kunz B, Mortara J, Sager P, Stockbridge N, Wright T, Finkle J, Krucoff M. The Cardiac Safety Research Consortium enters its second decade: An invitation to participate. American Heart Journal 2016;177:96 View
  42. Bollegala D, Maskell S, Sloane R, Hajne J, Pirmohamed M. Causality Patterns for Detecting Adverse Drug Reactions From Social Media: Text Mining Approach. JMIR Public Health and Surveillance 2018;4(2):e51 View
  43. Smith K, Golder S, Sarker A, Loke Y, O’Connor K, Gonzalez-Hernandez G. Methods to Compare Adverse Events in Twitter to FAERS, Drug Information Databases, and Systematic Reviews: Proof of Concept with Adalimumab. Drug Safety 2018;41(12):1397 View
  44. Tricco A, Zarin W, Lillie E, Jeblee S, Warren R, Khan P, Robson R, Pham B, Hirst G, Straus S. Utility of social media and crowd-intelligence data for pharmacovigilance: a scoping review. BMC Medical Informatics and Decision Making 2018;18(1) View
  45. Borchert J, Wang B, Ramzanali M, Stein A, Malaiyandi L, Dineley K. Adverse Events Due to Insomnia Drugs Reported in a Regulatory Database and Online Patient Reviews: Comparative Study. Journal of Medical Internet Research 2019;21(11):e13371 View
  46. Audeh B, Calvier F, Bellet F, Beyens M, Pariente A, Lillo-Le Louet A, Bousquet C. Pharmacology and social media: Potentials and biases of web forums for drug mention analysis—case study of France. Health Informatics Journal 2020;26(2):1253 View

Books/Policy Documents

  1. Dasgupta N, Winokur C, Pierce C. Communicating about Risks and Safe Use of Medicines. View
  2. Wang W, Cheung B, Leung Z, Chan K, See-To E. Multigenerational Online Behavior and Media Use. View
  3. Alimova I, Tutubalina E. Analysis of Images, Social Networks and Texts. View
  4. Alasmari A, Zhou L. Social Computing and Social Media. Communication and Social Communities. View
  5. Hasan S, Farri O. Data Science for Healthcare. View
  6. Motulsky A, Nikiema J, Bosson-Rieutort D. Multiple Perspectives on Artificial Intelligence in Healthcare. View