Prediction of adverse drug reactions using demographic and non-clinical drug characteristics in FAERS data

Abstract The presence of adverse drug reactions (ADRs) is an ongoing public health concern. While traditional methods to discover ADRs are very costly and limited, it is prudent to predict ADRs through non-invasive methods such as machine learning based on existing data. Although various studies exi...

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Bibliographic Details
Main Authors:	Alireza Farnoush, Zahra Sedighi-Maman, Behnam Rasoolian, Jonathan J. Heath, Banafsheh Fallah
Format:	Article
Language:	English
Published:	Nature Portfolio 2024-10-01
Series:	Scientific Reports
Subjects:	Adverse drug reactions Deep learning Random forest Machine learning Demographic features Non-clinical features
Online Access:	https://doi.org/10.1038/s41598-024-74505-2
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Prediction of adverse drug reactions using demographic and non-clinical drug characteristics in FAERS data

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