Abstract: Precisely predicting Drug-Drug Interactions (DDIs) carries the potential to elevate the quality and safety of drug therapies, protecting the well-being of patients, and providing essential ...
Abstract: Hybrid GNNs, which learn both long-term structural information encoded in static graphs and temporal interactions within dynamic graphs, have attracted attention for their high predictive ...
The mechanical behavior of viscoelastic materials is influenced, among other factors, by parameters like time and temperature. The present paper proposes a methodology for a thermorheologically and ...
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