Complementing the US Food and Drug Administration Adverse Event Reporting System With Adverse Drug Reaction Reporting From Social Media: Comparative Analysis

Journals

1. 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
2. Matsuda S, Ohtomo T, Tomizawa S, Miyano Y, Mogi M, Kuriki H, Nakayama T, Watanabe S. Incorporating Unstructured Patient Narratives and Health Insurance Claims Data in Pharmacovigilance: Natural Language Processing Analysis of Patient-Generated Texts About Systemic Lupus Erythematosus. JMIR Public Health and Surveillance 2021;7(6):e29238 View
3. Purushothaman V, McMann T, Li Z, Cuomo R, Mackey T. Content and trend analysis of user-generated nicotine sickness tweets: A retrospective infoveillance study. Tobacco Induced Diseases 2022;20(March):1 View
4. Oyebode O, Orji R. Identifying adverse drug reactions from patient reviews on social media using natural language processing. Health Informatics Journal 2023;29(1) View
5. Jarynowski A, Semenov A, Kamiński M, Belik V. Mild Adverse Events of Sputnik V Vaccine in Russia: Social Media Content Analysis of Telegram via Deep Learning. Journal of Medical Internet Research 2021;23(11):e30529 View
6. Chen T, Jia F, Yu Y, Zhang W, Wang C, Zhu S, Zhang N, Liu X. Potential Role of Quercetin in Polycystic Ovary Syndrome and Its Complications: A Review. Molecules 2022;27(14):4476 View
7. Venuturupalli S, Kumar A, Bunyan A, Davuluri N, Fortune N, Reuter K. Using Patient‐Reported Health Data From Social Media to Identify Diverse Lupus Patients and Assess Their Symptom and Medication Expressions: A Feasibility Study. Arthritis Care & Research 2023;75(2):365 View
8. Liu E, McCall K, Piper B. Variation in adverse drug events of opioids in the United States. Frontiers in Pharmacology 2023;14 View
9. Liang X, Li J, Anupindi R. Generic Drug Effectiveness: An Empirical Study on Health Service Utilization and Clinical Outcomes. SSRN Electronic Journal 2022 View
10. 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
11. Fisher A, Young M, Payer D, Pacheco K, Dubeau C, Mago V. Automating Detection of Drug-Related Harms on Social Media: Machine Learning Framework. Journal of Medical Internet Research 2023;25:e43630 View
12. Konkel K, Oner N, Ahmed A, Jones S, Berner E, Zengul F. Using natural language processing to characterize and predict homeopathic product-associated adverse events in consumer reviews: comparison to reports to FDA Adverse Event Reporting System (FAERS). Journal of the American Medical Informatics Association 2023;31(1):70 View
13. Du Y, Zhu J, Guo Z, Wang Z, Wang Y, Hu M, Zhang L, Yang Y, Wang J, Huang Y, Huang P, Chen M, Chen B, Yang C. Metformin adverse event profile: a pharmacovigilance study based on the FDA Adverse Event Reporting System (FAERS) from 2004 to 2022. Expert Review of Clinical Pharmacology 2024;17(2):189 View
14. Yuan Y, Kasson E, Taylor J, Cavazos-Rehg P, De Choudhury M, Aledavood T. Examining the Gateway Hypothesis and Mapping Substance Use Pathways on Social Media: Machine Learning Approach. JMIR Formative Research 2024;8:e54433 View
15. Leiter V. Signs and symptoms: Adverse events associated with a sterilization device. Social Science & Medicine 2024;351:116963 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. Guan X, Yang Y, Li X, Feng Y, Li J, Li X. Analysis of eplerenone in the FDA adverse event reporting system (FAERS) database: a focus on overall patient population and gender-specific subgroups. Frontiers in Pharmacology 2024;15 View
18. Postma D, Heijkoop M, De Smet P, Notenboom K, Leufkens H, Mantel-Teeuwisse A. Identifying Medicine Shortages With the Twitter Social Network: Retrospective Observational Study. Journal of Medical Internet Research 2024;26:e51317 View
19. Xu H, Xu N, Wang Y, Zou H, Wu S. A disproportionality analysis of low molecular weight heparin in the overall population and in pregnancy women using the FDA adverse event reporting system (FAERS) database. Frontiers in Pharmacology 2024;15 View
20. Fan Y, Wu T, Xu P, Yang C, An J, Zhang H, Abbas M, Dong X. Neratinib safety evaluation: real-world adverse event analysis from the FAERS database. Frontiers in Pharmacology 2024;15 View
21. Nezhurina E, Milchakov K, Abramova A. Social Media as a Source of Information for the Detection of Adverse Drug Reactions in Post-Marketing Surveillance: A Review. Safety and Risk of Pharmacotherapy 2024 View
22. Voloshchuk N, Zolotareva V, Hara A, Pashynska O, Taran I, Melnyk A, Denysiuk V. USING BIOPELLETS WITH METFORMIN IN THE EXPERIMENTAL METABOLIC SYNDROME. World of Medicine and Biology 2024;20(89):220 View
23. Jing Z, Hongyan X, Jingjing M, Mujuan P, Shiyu M, Ying S, Yan H. Adverse events associated with parenteral nutrition support therapy: A pharmacovigilance study. Journal of Parenteral and Enteral Nutrition 2024 View
24. Wei S, He C, Xie X, Zhang A, Tang S, Li S, He Y. Which fluoroquinolone is safer when combined with bedaquiline for tuberculosis treatment: evidence from FDA Adverse Event Reporting System database from 2013 to 2024. Frontiers in Pharmacology 2024;15 View

Books/Policy Documents

1. Chakraborty A, Venkatraman J. The Quintessence of Basic and Clinical Research and Scientific Publishing. View