Harnessing Social Media for Drug-Drug Interactions Detection

@article{Yang2013HarnessingSM,
  title={Harnessing Social Media for Drug-Drug Interactions Detection},
  author={Haodong Yang and Christopher C. Yang},
  journal={2013 IEEE International Conference on Healthcare Informatics},
  year={2013},
  pages={22-29}
}
  • Haodong Yang, Christopher C. Yang
  • Published in
    IEEE International Conference…
    2013
  • Medicine, Computer Science
  • Adverse drug reactions (ADRs) are causing a substantial amount of hospital admissions and deaths, which cannot be underestimated. Drug-drug interactions (DDIs) are an important patient safety problem and have been reported to cause a large portion of patient adverse events resulting in warning notices or the withdrawal of many drugs from the market. Currently, DDIs detection mainly depends on four kinds of data sources - clinical trial data, spontaneous reporting systems, electronic medical… CONTINUE READING

    Create an AI-powered research feed to stay up to date with new papers like this posted to ArXiv

    Citations

    Publications citing this paper.
    SHOWING 1-10 OF 23 CITATIONS

    Drug Recommendation toward Safe Polypharmacy

    VIEW 15 EXCERPTS
    CITES BACKGROUND
    HIGHLY INFLUENCED

    Discovering Drug-Drug Interactions and Associated Adverse Drug Reactions with Triad Prediction in Heterogeneous Healthcare Networks

    VIEW 5 EXCERPTS
    CITES METHODS & BACKGROUND

    Deep Learning for High-Order Drug-Drug Interaction Prediction

    VIEW 2 EXCERPTS
    CITES BACKGROUND

    Demographic Influence on Opioid Misuse

    VIEW 1 EXCERPT
    CITES BACKGROUND

    Big Data and Pharmacovigilance: Data Mining for Adverse Drug Events and Interactions.

    • C. Lee Ventola
    • Medicine
    • P & T : a peer-reviewed journal for formulary management
    • 2018

    Detecting adverse drug reactions from social media based on multi-channel convolutional neural networks

    VIEW 1 EXCERPT
    CITES BACKGROUND

    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 33 REFERENCES

    Data Mining Concepts and Techniques

    VIEW 3 EXCERPTS
    HIGHLY INFLUENTIAL

    A Potential Causal Association Mining Algorithm for Screening Adverse Drug Reactions in Postmarketing Surveillance

    VIEW 1 EXCERPT

    DrugBank 3.0: a comprehensive resource for ‘Omics’ research on drugs

    VIEW 1 EXCERPT