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

• In: Poster presentation
• At: Seoul (South Korea) (2017)
• Type: Poster
• Poster code: POS-HMIS-020
• 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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