Polypharmacy Side Effect Prediction with Graph Convolutional Neural Network based on Heterogeneous Structural and Biological Data
The prediction of polypharmacy side effects is crucial to reduce the mortality and morbidity of patients suffering from complex diseases. However, its experimental prediction is unfeasible due to the many possible drug combinations, leaving in silico tools as the most promising way of addressing thi...
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| Format: | Others |
| Language: | English |
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KTH, Numerisk analys, NA
2020
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| Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-288537 |