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Citing this Article

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Published on 10.07.15 in Vol 17, No 7 (2015): July

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

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

Jérémy Lardon, Redhouane Abdellaoui, Florelle Bellet, Hadyl Asfari, Julien Souvignet, Nathalie Texier, Marie-Christine Jaulent, Marie-Noëlle Beyens, Anita Burgun, Cédric Bousquet

J Med Internet Res 2015 (Jul 10); 17(7):e171 

According to Crossref, the following articles are citing this article (DOI 10.2196/jmir.4304):

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

  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
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  3. 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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  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
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  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
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  24. Bousquet C, Dahamna B, Guillemin-Lanne S, Darmoni SJ, 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
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  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
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  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
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  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;
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  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
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  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
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  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
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  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
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  33. Bravo , Li TS, Su AI, Good BM, Furlong LI. Combining machine learning, crowdsourcing and expert knowledge to detect chemical-induced diseases in text. Database 2016;2016:baw094
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  34. Sinha MS, Freifeld CC, Brownstein JS, Donneyong MM, Rausch P, Lappin BM, Zhou EH, Dal Pan GJ, Pawar AM, Hwang TJ, Avorn J, Kesselheim AS. 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
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  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
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  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
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  37. Sutphin C, Lee K, Yepes AJ, Uzuner , McInnes BT. Adverse drug event detection using reason assignments in FDA drug labels. Journal of Biomedical Informatics 2020;110:103552
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  38. Topaz M, Lai K, Dhopeshwarkar N, Seger DL, 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
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  39. . Big Data’s Role in Precision Public Health. Frontiers in Public Health 2018;6
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  40. Bhattacharya M, Snyder S, Malin M, Truffa MM, Marinic S, Engelmann R, Raheja RR. Using Social Media Data in Routine Pharmacovigilance: A Pilot Study to Identify Safety Signals and Patient Perspectives. Pharmaceutical Medicine 2017;31(3):167
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  41. Turner JR, Kowey PR, Rodriguez I, Cabell CH, Gintant G, Green CL, Kunz BL, Mortara J, Sager PT, Stockbridge N, Wright TJ, Finkle J, Krucoff MW. The Cardiac Safety Research Consortium enters its second decade: An invitation to participate. American Heart Journal 2016;177:96
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  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
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  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
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  44. Tricco AC, Zarin W, Lillie E, Jeblee S, Warren R, Khan PA, Robson R, Pham B, Hirst G, Straus SE. Utility of social media and crowd-intelligence data for pharmacovigilance: a scoping review. BMC Medical Informatics and Decision Making 2018;18(1)
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  45. Borchert JS, Wang B, Ramzanali M, Stein AB, Malaiyandi LM, Dineley KE. 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
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  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
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  47. Pathak R, Catalan-Matamoros D. Can Twitter posts serve as early indicators for potential safety signals? A retrospective analysis. International Journal of Risk & Safety in Medicine 2023;34(1):41
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  48. Coca JR, Coca-Asensio R, Esteban Bueno G. Socio-historical analysis of the social importance of pharmacovigilance. Frontiers in Sociology 2022;7
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  49. Dirkson A, den Hollander D, Verberne S, Desar I, Husson O, van der Graaf WTA, Oosten A, Reyners AKL, Steeghs N, van Loon W, van Oortmerssen G, Gelderblom H, Kraaij W. Sample Bias in Web-Based Patient-Generated Health Data of Dutch Patients With Gastrointestinal Stromal Tumor: Survey Study. JMIR Formative Research 2022;6(12):e36755
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  50. Takats C, Kwan A, Wormer R, Goldman D, Jones HE, Romero D. Ethical and Methodological Considerations of Twitter Data for Public Health Research: Systematic Review. Journal of Medical Internet Research 2022;24(11):e40380
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  51. Walsh J, Dwumfour C, Cave J, Griffiths F. Spontaneously generated online patient experience data - how and why is it being used in health research: an umbrella scoping review. BMC Medical Research Methodology 2022;22(1)
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  52. Dirkson A, Verberne S, Kraaij W, van Oortmerssen G, Gelderblom H. Automated gathering of real-world data from online patient forums can complement pharmacovigilance for rare cancers. Scientific Reports 2022;12(1)
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  53. . Computing Drug-Drug Similarity from Patient-Centric Data. Bioengineering 2023;10(2):182
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  54. Fossouo Tagne J, Yakob RA, Dang TH, Mcdonald R, Wickramasinghe N. Reporting, Monitoring, and Handling of Adverse Drug Reactions in Australia: Scoping Review. JMIR Public Health and Surveillance 2023;9:e40080
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  55. Gordijn R, Wessels W, Kriek E, Nicolai MPJ, Elzevier HW, Visser L, Guchelaar H, Teichert M. Patient reporting of sexual adverse events on an online platform for medication experiences. British Journal of Clinical Pharmacology 2022;88(12):5326
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  56. Yahya AA, Asiri Y, Alyami I, Asghar MZ. Social Media Analytics for Pharmacovigilance of Antiepileptic Drugs. Computational and Mathematical Methods in Medicine 2022;2022:1
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  57. Park S, Choi SH, Song Y, Kwon J. Comparison of Online Patient Reviews and National Pharmacovigilance Data for Tramadol-Related Adverse Events: Comparative Observational Study. JMIR Public Health and Surveillance 2022;8(1):e33311
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  58. Khademi Habibabadi S, Palmer C, Dimaguila GL, Javed M, Clothier HJ, Buttery J. Australasian Institute of Digital Health Summit 2022–Automated Social Media Surveillance for Detection of Vaccine Safety Signals: A Validation Study. Applied Clinical Informatics 2023;14(01):01
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  59. Shakeri Hossein Abad Z, Butler GP, Thompson W, Lee J. Crowdsourcing for Machine Learning in Public Health Surveillance: Lessons Learned From Amazon Mechanical Turk. Journal of Medical Internet Research 2022;24(1):e28749
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  60. Khademi Habibabadi S, Delir Haghighi P, Burstein F, Buttery J. Vaccine Adverse Event Mining of Twitter Conversations: 2-Phase Classification Study. JMIR Medical Informatics 2022;10(6):e34305
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  61. Keller R, Spanu A, Puhan MA, Flahault A, Lovis C, Mütsch M, Beau-Lejdstrom R. Social media and internet search data to inform drug utilization: A systematic scoping review. Frontiers in Digital Health 2023;5
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  62. Roche V, Robert J, Salam H. AI-Based Approach for Safety Signals Detection from Social Networks: Application to the Levothyrox Scandal in 2017 on Doctissimo Forum. SSRN Electronic Journal 2021;
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  63. 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
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  64. 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
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  65. Nwagwu W, Olayanju O. Aspects of Quality and Reliability of Ebola Virus Disease Information on Facebook. Mousaion: South African Journal of Information Studies 2023;41(1)
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  66. Lu Q, Schulz PJ, Chang A. Medication safety perceptions in China: Media exposure, healthcare experiences, and trusted information sources. Patient Education and Counseling 2024;123:108209
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  67. Wessel D, Pogrebnyakov N. Using Social Media as a Source of Real-World Data for Pharmaceutical Drug Development and Regulatory Decision Making. Drug Safety 2024;
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According to Crossref, the following books are citing this article (DOI 10.2196/jmir.4304):

  1. Dasgupta N, Winokur C, Pierce C. Communicating about Risks and Safe Use of Medicines. 2020. Chapter 11:307
    CrossRef
  2. Wang W, Cheung BC, Leung ZC, Chan K, See-To EW. Multigenerational Online Behavior and Media Use. 2019. chapter 92:1737
    CrossRef
  3. Alimova I, Tutubalina E. Analysis of Images, Social Networks and Texts. 2018. Chapter 1:3
    CrossRef
  4. Alasmari A, Zhou L. Social Computing and Social Media. Communication and Social Communities. 2019. Chapter 7:79
    CrossRef
  5. Hasan SA, Farri O. Data Science for Healthcare. 2019. Chapter 5:147
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  6. Motulsky A, Nikiema J, Bosson-Rieutort D. Multiple Perspectives on Artificial Intelligence in Healthcare. 2021. Chapter 8:91
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  7. Raghupathi V, Zhou Y, Raghupathi W. Research Anthology on Big Data Analytics, Architectures, and Applications. 2022. chapter 90:1843
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