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

Pharmacovigilance (134) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1641) Infodemiology and Infoveillance (1349) Natural Language Processing (692) Surveillance Systems (462) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1041) Machine Learning (1465)

Published on in Vol 4, No 2 (2018): Apr-Jun

Causality Patterns for Detecting Adverse Drug Reactions From Social Media: Text Mining Approach

Causality Patterns for Detecting Adverse Drug Reactions From Social Media: Text Mining Approach

Causality Patterns for Detecting Adverse Drug Reactions From Social Media: Text Mining Approach

Authors of this article:

Danushka Bollegala1 Author Orcid Image ;   Simon Maskell1 Author Orcid Image ;   Richard Sloane1 Author Orcid Image ;   Joanna Hajne1 Author Orcid Image ;   Munir Pirmohamed2 Author Orcid Image
Article Authors Cited by (23) Tweetations (10) Metrics

Journals

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  6. Routray R, Tetarenko N, Abu-Assal C, Mockute R, Assuncao B, Chen H, Bao S, Danysz K, Desai S, Cicirello S, Willis V, Alford S, Krishnamurthy V, Mingle E. Application of Augmented Intelligence for Pharmacovigilance Case Seriousness Determination. Drug Safety 2020;43(1):57 View
  7. Borchert J, Wang B, Ramzanali M, Stein A, Malaiyandi L, Dineley K. Adverse Events Due to Insomnia Drugs Reported in a Regulatory Database and Online Patient Reviews: Comparative Study. Journal of Medical Internet Research 2019;21(11):e13371 View
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  9. Wu J, Sivaraman V, Kumar D, Banda J, Sontag D. Pulse of the pandemic: Iterative topic filtering for clinical information extraction from social media. Journal of Biomedical Informatics 2021;120:103844 View
  10. Kayesh H, Islam M, Wang J, Ohira R, Wang Z. SCAN: A shared causal attention network for adverse drug reactions detection in tweets. Neurocomputing 2022;479:60 View
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  12. Walker L, Abuzour A, Bollegala D, Clegg A, Gabbay M, Griffiths A, Kullu C, Leeming G, Mair F, Maskell S, Relton S, Ruddle R, Shantsila E, Sperrin M, Van Staa T, Woodall A, Buchan I. The DynAIRx Project Protocol: Artificial Intelligence for dynamic prescribing optimisation and care integration in multimorbidity. Journal of Multimorbidity and Comorbidity 2022;12 View
  13. Ahne A, Khetan V, Tannier X, Rizvi M, Czernichow T, Orchard F, Bour C, Fano A, Fagherazzi G. Extraction of Explicit and Implicit Cause-Effect Relationships in Patient-Reported Diabetes-Related Tweets From 2017 to 2021: Deep Learning Approach. JMIR Medical Informatics 2022;10(7):e37201 View
  14. 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
  15. VanSchaik J, Jain P, Rajapuri A, Cheriyan B, Thyvalikakath T, Chakraborty S. Using transfer learning-based causality extraction to mine latent factors for Sjögren's syndrome from biomedical literature. Heliyon 2023;9(9):e19265 View
  16. Dey A, Shrivastava J, Kumar C. Classical-quantum hybrid transfer learning for adverse drug reaction detection from social media posts. Journal of Computational Social Science 2024;7(2):1433 View

Books/Policy Documents

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