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Media Contacts
A team of researchers has developed a novel, machine learning–based technique to explore and identify relationships among medical concepts using electronic health record data across multiple healthcare providers.
A team including researchers from the Department of Energy’s Oak Ridge National Laboratory has developed a digital tool to better monitor a condition known as Barrett’s esophagus, which affects more than 3 million people in the United States.
An analysis published in the Proceedings of the National Academy of Sciences and led by researchers from the U.S. Department of Energy’s Oak Ridge National Laboratory has received the 2021 Sustainability Science Award from the Ecological Society of America.
Researchers at Oak Ridge National Laboratory have identified a statistical relationship between the growth of cities and the spread of paved surfaces like roads and sidewalks. These impervious surfaces impede the flow of water into the ground, affecting the water cycle and, by extension, the climate.
Six ORNL scientists have been elected as fellows to the American Association for the Advancement of Science, or AAAS.
From materials science and earth system modeling to quantum information science and cybersecurity, experts in many fields run simulations and conduct experiments to collect the abundance of data necessary for scientific progress.
Research by an international team led by Duke University and the Department of Energy’s Oak Ridge National Laboratory scientists could speed the way to safer rechargeable batteries for consumer electronics such as laptops and cellphones.
A novel approach developed by scientists at ORNL can scan massive datasets of large-scale satellite images to more accurately map infrastructure – such as buildings and roads – in hours versus days.
To better determine the potential energy cost savings among connected homes, researchers at Oak Ridge National Laboratory developed a computer simulation to more accurately compare energy use on similar weather days.
A study led by Oak Ridge National Laboratory explored the interface between the Department of Veterans Affairs’ healthcare data system and the data itself to detect the likelihood of errors and designed an auto-surveillance tool