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1.	PDF Evans-Nathaniel-OHSU-ResearchWeek-2021 Creating interpretable and informative low-dimensional representations of cell-state from sequencing data using visible neural network variationa[...] Evans, Nathaniel ; McWeeney, Shannon Next generation sequencing (NGS) and single-cell sequencing technologies have enabled unparalleled resolution of the cell's molecular machinery; however, gleaning accurat [...] 2021 \| Abstract \| Detailed record - Similar records
2.	PDF Deep learning and structural MRI: in pursuit of improved prediction of self-regulatory behavior and mental health Harman, Gareth ; Kalpathy-Cramer, Jayashree ; Nagel, Bonnie ; Mooney, Michael[...] Nearly one in five children (17%) aged 2-8 were diagnosed with either a mental, emotional, developmental, or behavioral disorder in 2016 in the US. Early identification o [...] 2022-02-01 \| Dissertation \| Detailed record - Similar records
3.	PDF ResearchWeek.2020.Evans.Nathaniel Integrating domain knowledge, interpretable deep learning, and uncertainty quantification for computational prediction of cell response to drug c[...] Evans, Nathaniel ; Blucher, Aurora ; McWeeney, Shannon A major challenge in precision oncology is accurately modeling the molecular machinery that governs cellular sensitivity or resistance to a given drug or drug combination [...] 2020 \| Abstract \| Detailed record - Similar records
4.	PDF Evans.Nathaniel.2024 Mechanistic deep learning for perturbation biology: application to precision oncology Evans, Nathaniel J. ; McWeeney, Shannon ; Song, Xubo ; Wu, Guanming [...] The work presented in this dissertation focuses on the development of robust deep learning models to predict in-vitro cancer drug responses, with utility in precision onc [...] 2024-09-19 \| Dissertation \| Detailed record - Similar records

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