Predicting Drug-Drug Interactions Using Heterogeneous Graph Neural Networks: HGNN-DDI
Published in 4th International Conference on Signal Processing and Machine Learning, 2024
This paper presents HGNN-DDI, a novel framework leveraging heterogeneous graph neural networks to predict interactions between drugs. It demonstrates significant improvements in accuracy and reliability, offering potential applications in precision medicine and drug development.
Recommended citation: Hongbo Liu, Siyi Li, Zheng Yu. (2024). "Predicting Drug-Drug Interactions Using Heterogeneous Graph Neural Networks: HGNN-DDI." 4th International Conference on Signal Processing and Machine Learning.
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