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Blog posts : "machine learning"

Final acceptance of SOT 2022 session “Deep Learning and Graph Algorithms: New Approaches in Computational Toxicology”

Adrian Green and David Reif partnered with colleagues Carolyn Ring (U.S. EPA), John Wambaugh (U.S. EPA), and Alicia Frame (Neo4j) to propose the SOT session “Deep Learning and Graph Algorithms: New Approaches in Computational Toxicology”. The session has been finally accepted with the following deta…

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Leveraging high-throughput screening data, deep neural networks, and conditional generative adversarial networks to advance predictive toxicology (2021) PLoS Comput Biol

Green AJ, Mohlenkamp MJ, Das J, Chaudhari M, Truong L, Tanguay RL, et al. (2021) Leveraging high-throughput screening data, deep neural networks, and conditional generative adversarial networks to advance predictive toxicology. PLoS Comput Biol 17(7): e1009135. https://doi.org/10.1371/journal.pcbi.1…

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Nnamdi wins Best Poster award at 2021 Genomic Sciences Symposium!

Nnamdi Osakwe won the "Best Poster" award at the 2021 Genomic Science Symposium for his presentation entitled: "Building Comprehensive Models of Environmental Integrity" 

 

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Adrian presents seminar at Coffee & Viz seminar series

https://www.lib.ncsu.edu/events/coffee-viz-visualization-and-pattern-recognition-high-dimensional-zebrafish-behavioral

 

Coffee & Viz: Visualization and Pattern Recognition in High-Dimensional Zebrafish Behavioral Studies using Deep Learning

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The COVID-19 Pandemic Vulnerability Index (PVI) Dashboard: Monitoring County-Level Vulnerability Using Visualization, Statistical Modeling, and Machine Learning (2021) Environmental Health Perspectives

Marvel SW, House JS, Wheeler M, Song K, Zhou YH, Wright FA, Chiu WA, Rusyn I, Motsinger-Reif A, Reif DM. The COVID-19 Pandemic Vulnerability Index (PVI) Dashboard: Monitoring County-Level Vulnerability Using Visualization, Statistical Modeling, and Machine Learning. Environ Health Perspect. 2021 Jan…

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