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Tag: machine learning

Machine learning insights of anthropogenic and natural influences on riverbed deformation in a large lowland river

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AMANAMBU, MOSSA – Machine learning insights of anthropogenic and natural influences on riverbed deformation in a large lowland river Amobichukwu C. Amanambu, Joann Mossa Article first published online: 28 November 2023 DOI: https://doi.org/10.1016/j.geomorph.2023.108986 ABSTRACT: As escalating environmental pressures threaten the world’s river systems, understanding the driving factors influencing their geomorphological changes is of critical global […]

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The NASA Lab

The NASA Lab centers around the science of remote sensing and land system science/land change science using Earth observations for interdisciplinary research focused on global environmental change and human-environment interactions. Dr. Southworth’s NASA lab consists of undergraduate, master’s students, doctoral students and post-docs. The lab is run by Dr. Jane Southworth, Professor and Chair of […]

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Wildfires in the Arctic and tropical biomes: what is the relative role of climate?

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ENGSTRÖM, KEELLINGS – Wildfires in the Arctic and tropical biomes: what is the relative role of climate? Johanna Engström, Peyman Abbaszadeh, David Keellings, Proloy Deb, & Hamid Moradkhani Article first published online: 4 Jul 2022 DOI: https://doi.org/10.1007/s11069-022-05452-2 ABSTRACT: This study seeks to use machine learning to investigate the role of meteorological and climate variables on wildfire occurrence in […]

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Machine Learning Predictions of Dengue Patients Outcomes Yield Promising Results

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GAINESVILLE, FL – Helping patients with dengue can be challenging – especially in countries with multiple diseases spread by mosquitoes. Dengue, chikungunya, and Zika are viruses spread by the same type of mosquito; all three viruses are present in Ecuador and many other countries in Latin America and the Caribbean. Patients infected with one of […]

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Severity Index for Suspected Arbovirus (SISA): Machine learning for accurate prediction of hospitalization in subjects suspected of arboviral infection

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SIPPY, RYAN – Severity Index for Suspected Arbovirus (SISA): Machine learning for accurate prediction of hospitalization in subjects suspected of arboviral infection Rachel Sippy, Daniel F. Farrell, Daniel A. Lichtenstein, Ryan Nightingale, Megan A. Harris, Joseph Toth, Paris Hantztidiamantis, Nicholas Usher, Cinthya Cueva Aponte, Julio Barzallo Aguilar, Anthony Puthumana, Christina D. Lupone, Timothy Endy, Sadie […]

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