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Found 2 papers, 1 papers with code
Deep learning methods for drug response prediction in cancer: predominant and emerging trends
A wave of recent papers demonstrates promising results in predicting cancer response to drug treatments while utilizing deep learning methods.
Spatial Graph Attention and Curiosity-driven Policy for Antiviral Drug Discovery
We developed Distilled Graph Attention Policy Network (DGAPN), a reinforcement learning model to generate novel graph-structured chemical representations that optimize user-defined objectives by efficiently navigating a physically constrained domain.
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