Predicting adverse drug reactions through interpretable deep learning framework

Predicting adverse drug reactions through interpretable deep learning framework

Abstract Background Adverse drug reactions (ADRs) are unintended and harmful reactions caused by normal uses of drugs. Predicting and preventing ADRs in the early stage of the drug development pipeline can help to enhance drug safety and reduce financial costs. Methods In this paper, we developed ma...

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Bibliographic Details
Main Authors: Sanjoy Dey, Heng Luo, Achille Fokoue, Jianying Hu, Ping Zhang
Format: Article
Language:English
Published: BMC 2018-12-01
Series:BMC Bioinformatics
Subjects:
Chemical fingerprint
Adverse drug reaction
Deep learning
Online Access:http://link.springer.com/article/10.1186/s12859-018-2544-0

Internet

http://link.springer.com/article/10.1186/s12859-018-2544-0

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