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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; Burgos Edwards, Alberto JavierCONACYT Authority
Date of publishing
2018
Type of publication
info:eu-repo/semantics/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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