Published on in Vol 6, No 3 (2020): Jul-Sep
Preprints (earlier versions) of this paper are
available at
https://preprints.jmir.org/preprint/19266, first published
.
![Complementing the US Food and Drug Administration Adverse Event Reporting System With Adverse Drug Reaction Reporting From Social Media: Comparative Analysis Complementing the US Food and Drug Administration Adverse Event Reporting System With Adverse Drug Reaction Reporting From Social Media: Comparative Analysis](https://asset.jmir.pub/assets/7c05c9bb8f9b7f4429f95bc546073f5f.png 480w,https://asset.jmir.pub/assets/7c05c9bb8f9b7f4429f95bc546073f5f.png 960w,https://asset.jmir.pub/assets/7c05c9bb8f9b7f4429f95bc546073f5f.png 1920w,https://asset.jmir.pub/assets/7c05c9bb8f9b7f4429f95bc546073f5f.png 2500w)
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- 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
- 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
- Oyebode O, Orji R. Identifying adverse drug reactions from patient reviews on social media using natural language processing. Health Informatics Journal 2023;29(1):146045822211367 View
- 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
- 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
- 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
- Liu E, McCall K, Piper B. Variation in adverse drug events of opioids in the United States. Frontiers in Pharmacology 2023;14 View
- Liang X, Li J, Anupindi R. Generic Drug Effectiveness: An Empirical Study on Health Service Utilization and Clinical Outcomes. SSRN Electronic Journal 2022 View
- 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
- 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
- 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
- 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
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Books/Policy Documents
- Chakraborty A, Venkatraman J. The Quintessence of Basic and Clinical Research and Scientific Publishing. View