Use of Social Media for Pharmacovigilance Activities: Key Findings and Recommendations from the Vigi4Med Project
暂无分享,去创建一个
[1] M. Lindquist,et al. Quality criteria for early signals of possible adverse drug reactions , 1990, The Lancet.
[2] J. Hartigan,et al. A Bayesian Analysis for Change Point Problems , 1993 .
[3] Andrew Herxheimer,et al. Paroxetine, Panorama and user reporting of ADRs: Consumer intelligence matters in clinical practice and post-marketing drug surveillance , 2002 .
[4] Carlo Curino,et al. Mining officially unrecognized side effects of drugs by combining web search and machine learning , 2005, CIKM '05.
[5] B. Golomb,et al. Physician Response to Patient Reports of Adverse Drug Effects , 2007, Drug safety.
[6] S. Schröder,et al. Drug related problems with Antiparkinsonian agents: consumer Internet reports versus published data , 2007, Pharmacoepidemiology and drug safety.
[7] J. Moncrieff,et al. ACTA PSYCHIATRICA , 2006 .
[8] E. Larson,et al. Dissemination of health information through social networks: twitter and antibiotics. , 2010, American journal of infection control.
[9] Jian Yang,et al. Towards Internet-Age Pharmacovigilance: Extracting Adverse Drug Reactions from User Posts in Health-Related Social Networks , 2010, BioNLP@ACL.
[10] [One step more toward pharmacovigilance 2.0. Integration of web data community for a pharmacovigilance more alert]. , 2011, Presse medicale.
[11] Un pas de plus vers une pharmacovigilance 2.0 , 2011 .
[12] Richard B. Berlin,et al. Predicting adverse drug events from personal health messages. , 2011, AMIA ... Annual Symposium proceedings. AMIA Symposium.
[13] Robin E. Ferner,et al. Internet Accounts of Serious Adverse Drug Reactions , 2012, Drug Safety.
[14] Guideline on good pharmacovigilance practices ( GVP ) Module , 2013 .
[15] Mary S Vaughan Sarrazin,et al. Patient Perspectives of Dabigatran: Analysis of Online Discussion Forums , 2013, The Patient - Patient-Centered Outcomes Research.
[16] S J Stanhope,et al. Exploiting Online Discussions to Discover Unrecognized Drug Side Effects , 2013, Methods of Information in Medicine.
[17] Amit P. Sheth,et al. PREDOSE: A semantic web platform for drug abuse epidemiology using social media , 2013, J. Biomed. Informatics.
[18] L Pochard,et al. Analysis of patients' narratives posted on social media websites on benfluorex's (Mediator®) withdrawal in France , 2014, Journal of clinical pharmacy and therapeutics.
[19] Daniel Neagu,et al. Social media analysis for product safety using text mining and sentiment analysis , 2014, 2014 14th UK Workshop on Computational Intelligence (UKCI).
[20] M. Ibara,et al. Regulatory Definitions and Good Pharmacovigilance Practices in Social Media , 2015, Therapeutic innovation & regulatory science.
[21] A. Burgun,et al. Adverse Drug Reaction Identification and Extraction in Social Media: A Scoping Review , 2015, Journal of medical Internet research.
[22] Ronen Feldman,et al. Utilizing Text Mining on Online Medical Forums to Predict Label Change due to Adverse Drug Reactions , 2015, KDD.
[23] S. Golder,et al. Systematic review on the prevalence, frequency and comparative value of adverse events data in social media. , 2015, British journal of clinical pharmacology.
[24] Danushka Bollegala,et al. Social media and pharmacovigilance: A review of the opportunities and challenges. , 2015, British journal of clinical pharmacology.
[25] Kenneth H. Lai,et al. Clinicians’ Reports in Electronic Health Records Versus Patients’ Concerns in Social Media: A Pilot Study of Adverse Drug Reactions of Aspirin and Atorvastatin , 2016, Drug Safety.
[26] Christopher C. Yang,et al. Using Health-Consumer-Contributed Data to Detect Adverse Drug Reactions by Association Mining with Temporal Analysis , 2015, ACM Trans. Intell. Syst. Technol..
[27] Dragan Ilic,et al. The Acceptability Among Health Researchers and Clinicians of Social Media to Translate Research Evidence to Clinical Practice: Mixed-Methods Survey and Interview Study , 2015, Journal of medical Internet research.
[28] Rajesh Ghosh,et al. Aims and approaches of Web-RADR: a consortium ensuring reliable ADR reporting via mobile devices and new insights from social media , 2015, Expert opinion on drug safety.
[29] Wei Luo,et al. Guidelines for Developing and Reporting Machine Learning Predictive Models in Biomedical Research: A Multidisciplinary View , 2016, Journal of medical Internet research.
[30] Rachel E. Ginn,et al. Social Media Mining for Toxicovigilance: Automatic Monitoring of Prescription Medication Abuse from Twitter , 2016, Drug Safety.
[31] Marc Van Audenrode,et al. Can social media data lead to earlier detection of drug‐related adverse events? , 2016, Pharmacoepidemiology and drug safety.
[32] Pierre Zweigenbaum,et al. Identification of Drug-Related Medical Conditions in Social Media , 2016, LREC.
[33] Vagelis Hristidis,et al. Demographic-Based Content Analysis of Web-Based Health-Related Social Media , 2016, Journal of medical Internet research.
[34] Olivier Blin,et al. Investigating patient narratives posted on Internet and their informativeness level for pharmacovigilance purpose: The example of comments about statins. , 2017, Therapie.
[35] Christopher C. Yang,et al. Automated Off-label Drug Use Detection from User Generated Content , 2017, BCB.
[36] Eric R. LaRose,et al. Adverse Drug Event Discovery Using Biomedical Literature: A Big Data Neural Network Adventure , 2017, JMIR medical informatics.
[37] Michel Beigbeder,et al. Vigi4Med Scraper: A Framework for Web Forum Structured Data Extraction and Semantic Representation , 2017, PloS one.
[38] Jeffery L Painter,et al. Using Social Listening Data to Monitor Misuse and Nonmedical Use of Bupropion: A Content Analysis , 2017, JMIR public health and surveillance.
[39] Melissa M. Truffa,et al. Using Social Media Data in Routine Pharmacovigilance: A Pilot Study to Identify Safety Signals and Patient Perspectives , 2017, Pharmaceutical Medicine.
[40] Anne Cocos,et al. Deep learning for pharmacovigilance: recurrent neural network architectures for labeling adverse drug reactions in Twitter posts , 2017, J. Am. Medical Informatics Assoc..
[41] Julien Souvignet,et al. The Adverse Drug Reactions from Patient Reports in Social Media Project: Five Major Challenges to Overcome to Operationalize Analysis and Efficiently Support Pharmacovigilance Process , 2017, JMIR research protocols.
[42] Gregory E. Powell,et al. Enabling social listening for cardiac safety monitoring: Proceedings from a drug information association–cardiac safety research consortium cosponsored think tank , 2017, American heart journal.
[43] Marina Lengsavath,et al. Social Media Monitoring and Adverse Drug Reaction Reporting in Pharmacovigilance , 2017, Therapeutic innovation & regulatory science.
[44] Jingcheng Du,et al. Leveraging machine learning-based approaches to assess human papillomavirus vaccination sentiment trends with Twitter data , 2017, BMC Medical Informatics and Decision Making.
[45] G. Niklas Norén,et al. Assessment of the Utility of Social Media for Broad-Ranging Statistical Signal Detection in Pharmacovigilance: Results from the WEB-RADR Project , 2018, Drug Safety.
[46] Davy Weissenbacher,et al. Pharmacoepidemiologic Evaluation of Birth Defects from Health-Related Postings in Social Media During Pregnancy , 2018, Drug Safety.
[47] Graeme Hirst,et al. Utility of social media and crowd-intelligence data for pharmacovigilance: a scoping review , 2018, BMC Medical Informatics and Decision Making.
[48] M. Keller,et al. Reproductive Health and Medication Concerns for Patients With Inflammatory Bowel Disease: Thematic and Quantitative Analysis Using Social Listening , 2018, Journal of medical Internet research.
[49] So Hyun Park,et al. Identification of Primary Medication Concerns Regarding Thyroid Hormone Replacement Therapy From Online Patient Medication Reviews: Text Mining of Social Network Data , 2018, Journal of medical Internet research.
[50] F. Bellet,et al. Comment on “Assessment of the Utility of Social Media for Broad-Ranging Statistical Signal Detection in Pharmacovigilance: Results from the WEB-RADR Project” , 2018, Drug Safety.
[51] P. Myint,et al. The pale evidence for treatment of iron-deficiency anaemia in older people , 2018, Therapeutic advances in drug safety.
[52] Christopher C. Yang,et al. Exploiting OHC Data with Tensor Decomposition for Off-Label Drug Use Detection , 2018, 2018 IEEE International Conference on Healthcare Informatics (ICHI).
[53] R. Azam. Accessing social media information for pharmacovigilance: what are the ethical implications? , 2018, Therapeutic advances in drug safety.
[54] Berry de Bruijn,et al. Data and systems for medication-related text classification and concept normalization from Twitter: insights from the Social Media Mining for Health (SMM4H)-2017 shared task , 2018, J. Am. Medical Informatics Assoc..
[55] Goran Nenadic,et al. Frequent discussion of insomnia and weight gain with glucocorticoid therapy: an analysis of Twitter posts , 2017, npj Digital Medicine.
[56] Xavier Rafael-Palou,et al. Comparative analysis of predictive methods for early assessment of compliance with continuous positive airway pressure therapy , 2018, BMC Medical Informatics and Decision Making.
[57] Natalia Grabar,et al. Detection and Analysis of Drug Misuses. A Study Based on Social Media Messages , 2018, Front. Pharmacol..
[58] C. Blandizzi,et al. The usefulness of listening social media for pharmacovigilance purposes: a systematic review , 2018, Expert opinion on drug safety.
[59] H. Riper,et al. Behind the Scenes of Online Therapeutic Feedback in Blended Therapy for Depression: Mixed-Methods Observational Study , 2018, Journal of medical Internet research.
[60] J. Slattery,et al. An algorithm to detect unexpected increases in frequency of reports of adverse events in EudraVigilance , 2017, Pharmacoepidemiology and drug safety.
[61] Anita Burgun,et al. Detection of Cases of Noncompliance to Drug Treatment in Patient Forum Posts: Topic Model Approach , 2018, Journal of medical Internet research.
[62] Sue Rees,et al. Using social media in safety signal management: is it reliable? , 2018, Therapeutic advances in drug safety.
[63] Fabio Vivarelli,et al. Geraniol Pharmacokinetics, Bioavailability and Its Multiple Effects on the Liver Antioxidant and Xenobiotic-Metabolizing Enzymes , 2018, Front. Pharmacol..
[64] N. Shah,et al. Detecting Chemotherapeutic Skin Adverse Reactions in Social Health Networks Using Deep Learning , 2018, JAMA oncology.
[65] S. Golder,et al. Methods to Compare Adverse Events in Twitter to FAERS, Drug Information Databases, and Systematic Reviews: Proof of Concept with Adalimumab , 2018, Drug Safety.
[66] Cyril Grouin,et al. Descriptions of Adverse Drug Reactions Are Less Informative in Forums Than in the French Pharmacovigilance Database but Provide More Unexpected Reactions , 2018, Front. Pharmacol..
[67] M. Jaulent,et al. Evaluating Twitter as a complementary data source for pharmacovigilance , 2018, Expert opinion on drug safety.
[68] Cédric Bousquet,et al. Signal Detection for Baclofen in Web Forums: A Preliminary Study , 2018, MIE.
[69] Cartic Ramakrishnan,et al. Sorting Through the Safety Data Haystack: Using Machine Learning to Identify Individual Case Safety Reports in Social-Digital Media , 2018, Drug Safety.
[70] H. Dolk,et al. An assessment of pregnant women's knowledge and use of the Internet for medication safety information and purchase , 2018, Journal of advanced nursing.
[71] Andrew Bate,et al. The hope, hype and reality of Big Data for pharmacovigilance , 2018, Therapeutic advances in drug safety.
[72] Pierre Zweigenbaum,et al. Initial Experiments for Pharmacovigilance Analysis in Social Media Using Summaries of Product Characteristics , 2019, MedInfo.
[73] Marina Lengsavath,et al. Establishing a Framework for the Use of Social Media in Pharmacovigilance in Europe , 2019, Drug Safety.
[74] N. Chavannes,et al. Electronic Health Self-Management Interventions for Patients With Chronic Kidney Disease: Systematic Review of Quantitative and Qualitative Evidence , 2019, Journal of medical Internet research.
[75] M. Benkebil,et al. Benefits of combining change‐point analysis with disproportionality analysis in pharmacovigilance signal detection , 2018, Pharmacoepidemiology and drug safety.
[76] S. Golder,et al. Understanding Public Attitudes Toward Researchers Using Social Media for Detecting and Monitoring Adverse Events Data: Multi Methods Study , 2019, Journal of medical Internet research.
[77] S. Tcherny-Lessenot,et al. Comparison of text processing methods in social media–based signal detection , 2019, Pharmacoepidemiology and drug safety.
[78] V. Welch,et al. Using Social Media to Uncover Treatment Experiences and Decisions in Patients With Acute Myeloid Leukemia or Myelodysplastic Syndrome Who Are Ineligible for Intensive Chemotherapy: Patient-Centric Qualitative Data Analysis , 2019, Journal of medical Internet research.
[79] Pierre Zweigenbaum,et al. French Levothyrox® Crisis: Retrospective Analysis of Social Media , 2019 .
[80] N. Shah,et al. Early Detection of Adverse Drug Reactions in Social Health Networks: A Natural Language Processing Pipeline for Signal Detection , 2019, JMIR public health and surveillance.
[81] Evgeny A. Antipov,et al. The effects of adverse drug reactions on patients' satisfaction: Evidence from publicly available data on Tamiflu (oseltamivir) , 2019, Int. J. Medical Informatics.
[82] Natalia Grabar,et al. Detecting Drug Non-Compliance in Internet Fora Using Information Retrieval and Machine Learning Approaches , 2019, MedInfo.
[83] H. Zeilhofer,et al. Social Media Surveillance of Multiple Sclerosis Medications Used During Pregnancy and Breastfeeding: Content Analysis , 2019, Journal of medical Internet research.
[84] Antoni F. Z. Wisniewski,et al. Recommendations for the Use of Social Media in Pharmacovigilance: Lessons from IMI WEB-RADR , 2019, Drug Safety.
[85] Dimitra Pappa,et al. Harnessing social media data for pharmacovigilance: a review of current state of the art, challenges and future directions , 2019, International Journal of Data Science and Analytics.
[86] Abeed Sarker,et al. Mining social media for prescription medication abuse monitoring: a review and proposal for a data-centric framework , 2019, J. Am. Medical Informatics Assoc..
[87] A. Pariente,et al. Pharmacology and social media: Potentials and biases of web forums for drug mention analysis—case study of France , 2019, Health Informatics J..