MFHG-DDI: An Enhanced Hybrid Graph Method Leveraging Multiple Features for Predicting Drug–Drug Interactions

MFHG-DDI: An Enhanced Hybrid Graph Method Leveraging Multiple Features for Predicting Drug–Drug Interactions

Drug-drug interactions (DDIs) can severely affect patient health and safety. Predicting potential DDIs before administering medication to patients is crucial for drug development as it helps to prevent adverse drug reactions. Many effective DDI prediction methods have been proposed using graph neura...

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Bibliographic Details
Main Authors: Xiang Li, Xiangmin Ji, Chengzhen Xu, Jie Hou, Xiaoyu Zhao, Guodong Peng
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Drug-drug interaction
multiple features
heterogeneous network
graph convolutional network
graph attention network
Online Access:https://ieeexplore.ieee.org/document/10786969/
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https://ieeexplore.ieee.org/document/10786969/

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