Articles with "models trained" as a keyword



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Deep reinforcement learning for de novo drug design

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Published in 2018 at "Science Advances"

DOI: 10.1126/sciadv.aap7885

Abstract: We introduce an artificial intelligence approach to de novo design of molecules with desired physical or biological properties. We have devised and implemented a novel computational strategy for de novo design of molecules with desired… read more here.

Keywords: models trained; design; reinforcement learning; deep reinforcement ... See more keywords
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SMILES-based deep generative scaffold decorator for de-novo drug design

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Published in 2020 at "Journal of Cheminformatics"

DOI: 10.1186/s13321-020-00441-8

Abstract: Molecular generative models trained with small sets of molecules represented as SMILES strings can generate large regions of the chemical space. Unfortunately, due to the sequential nature of SMILES strings, these models are not able… read more here.

Keywords: models trained; smiles based; scaffold; chemistry ... See more keywords
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Using Adversarial Images to Assess the Robustness of Deep Learning Models Trained on Diagnostic Images in Oncology

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Published in 2022 at "JCO Clinical Cancer Informatics"

DOI: 10.1200/cci.21.00170

Abstract: PURPOSE Deep learning (DL) models have rapidly become a popular and cost-effective tool for image classification within oncology. A major limitation of DL models is their vulnerability to adversarial images, manipulated input images designed to… read more here.

Keywords: robustness models; oncology; learning models; deep learning ... See more keywords