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A Recommender System Approach for Predicting Drug Side Effects

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URI
http://hdl.handle.net/20.500.14066/2996
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Author(s)
Galeano Galeano, Diego ArielCONACYT Authority; Paccanaro, AlbertoCONACYT Authority
Date of publishing
2018
Type of publication
research article
Subject(s)
DRUG
SIDE EFFECTS
RECOMMENDATION SYSTEMS
ADVERSE DRUG EVENTS
LATENT FACTOR MODEL
COLLABORATIVE FILTERING
 
Abstract
The accurate identification of drug side effects represents a major concern for public health. We propose a collaborative filtering model for large-scale prediction of drug side effects. Our approach provides side effects recommendations for drugs to safety professionals. The proposed latent factor model relies solely on the public drug-side effect relationships from safety data.
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