| P50 | author | Anita Burgun | Q51753128 |
| | Marie-Christine Jaulent | Q56395903 |
| | Marie-Noëlle Beyens | Q57207953 |
| | Julien Souvignet | Q57208017 |
| | Redhouane Abdellaoui | Q58412717 |
| | Nathalie Texier | Q88058330 |
| | Jérémy Lardon | Q89504022 |
| | Florelle Bellet | Q89504024 |
| | Hadyl Asfari | Q96276877 |
| | Cédric Bousquet | Q50419515 |
| P2093 | author name string | Hadyl Asfari | |
| | Jérémy Lardon | |
| | Julien Souvignet | |
| | Florelle Bellet | |
| | Marie-Noëlle Beyens | |
| | Nathalie Texier | |
| | Redhouane Abdellaoui | |
| P2860 | cites work | Scoping studies: towards a methodological framework | Q24570441 |
| | Scoping studies: advancing the methodology | Q24570529 |
| | Using text-mining techniques in electronic patient records to identify ADRs from medicine use | Q26864161 |
| | Adverse drug reactions as cause of admission to hospital: prospective analysis of 18 820 patients | Q28169189 |
| | A pipeline to extract drug-adverse event pairs from multiple data sources | Q28658495 |
| | Postmarket drug surveillance without trial costs: discovery of adverse drug reactions through large-scale analysis of web search queries | Q28677138 |
| | Incidence of adverse drug reactions in hospitalized patients: a meta-analysis of prospective studies | Q29616299 |
| | Dictionary construction and identification of possible adverse drug events in Danish clinical narrative text | Q30002316 |
| | PatientsLikeMe: Consumer health vocabulary as a folksonomy | Q30854132 |
| | Drug related problems with Antiparkinsonian agents: consumer Internet reports versus published data | Q31111908 |
| | The subjective experience of taking antipsychotic medication: a content analysis of Internet data | Q33409973 |
| | Agencies use social media to track foodborne illness. | Q51458194 |
| | Analysis of patients' narratives posted on social media websites on benfluorex's (Mediator® ) withdrawal in France. | Q51462308 |
| | Can social media benefit drug safety? | Q51474300 |
| | The proportion of patient reports of suspected ADRs to signal detection in the Netherlands: case-control study. | Q53897535 |
| | Power and weakness of spontaneous reporting: a probabilistic approach | Q68101463 |
| | [One step more toward pharmacovigilance 2.0. Integration of web data community for a pharmacovigilance more alert] | Q84622811 |
| | Towards Large-scale Twitter Mining for Drug-related Adverse Events | Q89116722 |
| | A support package for parents of excessively crying infants: development and feasibility study | Q95826186 |
| | Data mining on electronic health record databases for signal detection in pharmacovigilance: which events to monitor? | Q33503787 |
| | Digital drug safety surveillance: monitoring pharmaceutical products in twitter | Q33579843 |
| | A context-blocks model for identifying clinical relationships in patient records | Q33928259 |
| | Enhancing the scoping study methodology: a large, inter-professional team's experience with Arksey and O'Malley's framework | Q34632885 |
| | Detecting adverse events using information technology | Q34775765 |
| | Mining adverse drug reactions from online healthcare forums using hidden Markov model | Q34812232 |
| | Online discussion of drug side effects and discontinuation among breast cancer survivors | Q35233959 |
| | Ranking adverse drug reactions with crowdsourcing. | Q35289332 |
| | Identifying potential adverse effects using the web: a new approach to medical hypothesis generation | Q35504449 |
| | Can online consumers contribute to drug knowledge? A mixed-methods comparison of consumer-generated and professionally controlled psychotropic medication information on the internet | Q35567642 |
| | Patients as a direct source of information on adverse drug reactions | Q35703486 |
| | Patients' role in reporting adverse drug reactions | Q35842579 |
| | Patient reporting of suspected adverse drug reactions: a review of published literature and international experience. | Q36024366 |
| | Automated acquisition of disease drug knowledge from biomedical and clinical documents: an initial study | Q36508511 |
| | Designing and evaluating a clustering system for organizing and integrating patient drug outcomes in personal health messages | Q36519059 |
| | Intensive monitoring of duloxetine: results of a web-based intensive monitoring study | Q36542573 |
| | Tweaking and tweeting: exploring Twitter for nonmedical use of a psychostimulant drug (Adderall) among college students | Q36795041 |
| | An exploration of social circles and prescription drug abuse through Twitter | Q37204691 |
| | Patient perspectives of dabigatran: analysis of online discussion forums. | Q37268085 |
| | A method for controlling complex confounding effects in the detection of adverse drug reactions using electronic health records | Q37598934 |
| | Adverse drug reaction reporting by patients: an overview of fifty countries | Q38205725 |
| | Potential of social media as a tool to combat foodborne illness | Q38225763 |
| | Health department use of social media to identify foodborne illness - Chicago, Illinois, 2013-2014. | Q38239756 |
| | Characteristics of consumer terminology for health information retrieval | Q38431678 |
| | Extraction of potential adverse drug events from medical case reports | Q38459298 |
| | Pattern mining for extraction of mentions of Adverse Drug Reactions from user comments. | Q39929592 |
| | Random models for margins of a 2 x 2 contingency table and application to pharmacovigilance | Q41158958 |
| | Undesirable effects related to oral antineoplastic drugs: comparison between patients' internet narratives and a national pharmacovigilance database | Q42672233 |
| | Exploiting online discussions to discover unrecognized drug side effects | Q43981177 |
| | Extraction of adverse drug effects from clinical records | Q44312930 |
| | 'Global trigger tool' shows that adverse events in hospitals may be ten times greater than previously measured | Q44511331 |
| | Quality criteria for early signals of possible adverse drug reactions | Q44656748 |
| | Internet accounts of serious adverse drug reactions: a study of experiences of Stevens-Johnson syndrome and toxic epidermal necrolysis. | Q47951342 |
| P275 | copyright license | Creative Commons Attribution 2.0 Generic | Q19125117 |
| P6216 | copyright status | copyrighted | Q50423863 |
| P433 | issue | 7 | |
| P407 | language of work or name | English | Q1860 |
| P921 | main subject | adverse drug reaction | Q45959 |
| | social media | Q202833 |
| | scoping review | Q101116078 |
| P304 | page(s) | e171 | |
| P577 | publication date | 2015-07-10 | |
| P1433 | published in | Journal of Medical Internet Research | Q6295534 |
| P1476 | title | Adverse Drug Reaction Identification and Extraction in Social Media: A Scoping Review | |
| P478 | volume | 17 | |