From pixels to prognosis: leveraging radiomics and machine learning to predict IDH1 genotype in gliomas. [PDF]
Karakas AB+5 more
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A beginner's approach to deep learning applied to VS and MD techniques. [PDF]
D'Hondt S, Oramas J, De Winter H.
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Integrating QSAR modelling with reinforcement learning for Syk inhibitor discovery. [PDF]
Zavadskaya M+3 more
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Tracking protein kinase targeting advances: integrating QSAR into machine learning for kinase-targeted drug discovery. [PDF]
Shahin R, Jaafreh S, Azzam Y.
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Publishing neural networks in drug discovery might compromise training data privacy. [PDF]
Krüger FP+4 more
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AI/ML methodologies and the future-will they be successful in designing the next generation of new chemical entities? [PDF]
Bienstock RJ.
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Protecting your skin: a highly accurate LSTM network integrating conjoint features for predicting chemical-induced skin irritation. [PDF]
Duy HA, Srisongkram T.
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E-GuARD: expert-guided augmentation for the robust detection of compounds interfering with biological assays. [PDF]
Palmacci V+5 more
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Predicting overall survival in glioblastoma patients using machine learning: an analysis of treatment efficacy and patient prognosis. [PDF]
Onciul R+7 more
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A data driven predictive viscosity model for the microemulsion phase. [PDF]
Talapatra A, Nojabaei B, Khodaparast P.
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