ArticleRSC advances2024
MMSSC-Net: multi-stage sequence cognitive networks for drug molecule recognition.
Article in RSC advances, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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5 authors.
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Abstract
In the growing body of scientific literature, the structure and information of drugs are usually represented in two-dimensional vector graphics. Drug compound structures in vector graphics form are difficult to recognize and utilize by computers. Although the current OCSR paradigm has shown good performance, most existing work treats it as a single isolated whole. This paper proposes a multi-stage cognitive neural network model that predicts molecular vector graphics more finely. Based on cognitive methods, we construct a model for fine-grained perceptual representation of molecular images from bottom to top, and in stages, the primary representation of atoms and bonds is potential discrete label sequence (atom type, bond type, functional group,
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