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

Pharmacovigilance (134) Infodemiology and Infoveillance (1349) Natural Language Processing (692) Adverse Drug Events Detection, Pharmacovigilance and Surveillance (156) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1041)

Published on in Vol 3, No 2 (2017): Apr-Jun

Filtering Entities to Optimize Identification of Adverse Drug Reaction From Social Media: How Can the Number of Words Between Entities in the Messages Help?

Filtering Entities to Optimize Identification of Adverse Drug Reaction From Social Media: How Can the Number of Words Between Entities in the Messages Help?

Filtering Entities to Optimize Identification of Adverse Drug Reaction From Social Media: How Can the Number of Words Between Entities in the Messages Help?

Authors of this article:

Redhouane Abdellaoui1, 2 Author Orcid Image ;   Stéphane Schück2 Author Orcid Image ;   Nathalie Texier2 Author Orcid Image ;   Anita Burgun1, 3 Author Orcid Image
Article Authors Cited by (20) Tweetations (6) Metrics

Journals

  1. Kürzinger M, Schück S, Texier N, Abdellaoui R, Faviez C, Pouget J, Zhang L, Tcherny-Lessenot S, Lin S, Juhaeri J. Web-Based Signal Detection Using Medical Forums Data in France: Comparative Analysis. Journal of Medical Internet Research 2018;20(11):e10466 View
  2. Pappa D, Stergioulas L. Harnessing social media data for pharmacovigilance: a review of current state of the art, challenges and future directions. International Journal of Data Science and Analytics 2019;8(2):113 View
  3. Li F, Liu W, Yu H. Extraction of Information Related to Adverse Drug Events from Electronic Health Record Notes: Design of an End-to-End Model Based on Deep Learning. JMIR Medical Informatics 2018;6(4):e12159 View
  4. Mavragani A. Infodemiology and Infoveillance: Scoping Review. Journal of Medical Internet Research 2020;22(4):e16206 View
  5. Schäfer F, Faviez C, Voillot P, Foulquié P, Najm M, Jeanne J, Fagherazzi G, Schück S, Le Nevé B. Mapping and Modeling of Discussions Related to Gastrointestinal Discomfort in French-Speaking Online Forums: Results of a 15-Year Retrospective Infodemiology Study. Journal of Medical Internet Research 2020;22(11):e17247 View
  6. 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 View
  7. 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 View
  8. Bousquet C, Dahamna B, Guillemin-Lanne S, Darmoni S, 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 View
  9. 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 View
  10. Schück S, Roustamal A, Gedik A, Voillot P, Foulquié P, Penfornis C, Job B. Assessing Patient Perceptions and Experiences of Paracetamol in France: Infodemiology Study Using Social Media Data Mining. Journal of Medical Internet Research 2021;23(7):e25049 View
  11. Arquembourg J, Glaser P, Roblot F, Metzler I, Gallant-Dewavrin M, Mebarki A, Voillot P, Schück S, Lalaude O. Social Media Platforms Listening Study on Antibiotic Resistance: Quantitative and Qualitative Findings. (Preprint). JMIR Formative Research 2022 View
  12. Renner S, Marty T, Khadhar M, Foulquié P, Voillot P, Mebarki A, Montagni I, Texier N, Schück S. A New Method to Extract Health-Related Quality of Life Data From Social Media Testimonies: Algorithm Development and Validation. Journal of Medical Internet Research 2022;24(1):e31528 View
  13. Déguilhem A, Malaab J, Talmatkadi M, Renner S, Foulquié P, Fagherazzi G, Loussikian P, Marty T, Mebarki A, Texier N, Schuck S. Identifying Profiles and Symptoms of Patients With Long COVID in France: Data Mining Infodemiology Study Based on Social Media. JMIR Infodemiology 2022;2(2):e39849 View
  14. Voillot P, Riche B, Portafax M, Foulquié P, Gedik A, Barbarot S, Misery L, Héas S, Mebarki A, Texier N, Schück S. Social Media Platforms Listening Study on Atopic Dermatitis: Quantitative and Qualitative Findings. Journal of Medical Internet Research 2022;24(1):e31140 View
  15. Kaas‐Hansen B, Placido D, Rodríguez C, Thorsen‐Meyer H, Gentile S, Nielsen A, Brunak S, Jürgens G, Andersen S. Language‐agnostic pharmacovigilant text mining to elicit side effects from clinical notes and hospital medication records. Basic & Clinical Pharmacology & Toxicology 2022;131(4):282 View
  16. Goadsby P, Ruiz de la Torre E, Constantin L, Amand C. Social Media Listening and Digital Profiling Study of People With Headache and Migraine: Retrospective Infodemiology Study. Journal of Medical Internet Research 2023;25:e40461 View
  17. 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 View
  18. Faviez C, Talmatkadi M, Foulquié P, Mebarki A, Schück S, Burgun A, Chen X. Assessment of the Early Detection of Anosmia and Ageusia Symptoms in COVID-19 on Twitter: Retrospective Study. JMIR Infodemiology 2023;3:e41863 View
  19. Karapetiantz P, Audeh B, Redjdal A, Tiffet T, Bousquet C, Jaulent M. Monitoring Adverse Drug Events in Web Forums: Evaluation of a Pipeline and Use Case Study. Journal of Medical Internet Research 2024;26:e46176 View

Books/Policy Documents

  1. Dasgupta N, Winokur C, Pierce C. Communicating about Risks and Safe Use of Medicines. View