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Accurate and interpretable drug-drug interaction prediction enabled by knowledge subgraph learning - Communications Medicine

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Accurate and interpretable drug-drug interaction prediction enabled by knowledge subgraph learning - Communications Medicine

Discovering potential drug-drug interactions (DDIs) is a long-standing challenge in clinical treatments and drug developments. Recently, deep learning techniques have been developed for DDI prediction. However, they generally require a huge number of samples, while known DDIs are rare. In this work, we present KnowDDI, a graph neural network-based method that addresses the above challenge.

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Accurate and interpretable drug-drug interaction prediction enabled by knowledge subgraph learning - Communications Medicine

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Accurate and interpretable drug-drug interaction prediction enabled by knowledge subgraph learning - Communications Medicine

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Unlocking the Power of Knowledge
for Humanity's Progress