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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.. The access to the whole abstract and if available the presentation file is available to FIP members and to congress participants of that specific congress.
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Last update 28 September 2023