Reducing the clinical costs of adverse drug reactions using ai deep learning

  • At: 2017 FIP Congress in Seoul (South Korea)
  • Type: Poster
  • By: OH, Jeongeun (Ewha Womans University, College of pharmacy, Seoul, Korea, Republic Of)
  • Co-author(s): Jeongeun Oh: College of Pharmacy, Ewha Womans University, Korea, Republic Of
    So Young Jeon: College of Pharmacy, Ewha Womans University, Korea, Republic Of
    Ji Young Oh: College of Pharmacy, Ewha Womans University, Korea, Republic Of
    Minhyoung Ahn: College of Pharmacy, Ewha Womans University, Korea, Republic Of
  • Abstract:

    Background

    The clinical cost of adverse drug reactions (ADRs) is currently a global issue. To reduce this cost, it is crucial to predict ADRs during clinical trials.

    Purpose

    This study aims to seek for solution to reduce costs of ADR by using the FDA Adverse Event Reporting System (FAERS), the All of Us Research Program, and Artificial Intelligence..

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