DHS) Science and Technology Directorate (S&T) awarded $199,536 Phase 1 funding to Analytical AI of Birmingham, Alabama.
The San Diego Supercomputer Center at the University of California San Diego is providing priority access to its high-performance computer systems and other resources to researchers advancing our understanding of the virus and efforts to develop an effective vaccine in as short a time as possible.
With advanced computer vision models and live public street cam video, a University of Michigan startup is tracking social distancing behaviors in real time at some of the most visited places in the world.
With support from Amazon Web Services, UC San Diego Health physicians are using AI in a clinical research study aimed at speeding the detection of pneumonia, a condition associated with severe COVID-19.
Bioengineers have combined standard microscopy, infrared light, and artificial intelligence to assemble digital biopsies that identify important molecular characteristics of cancer biopsy samples.
Argonne researchers have invented a machine-learning based algorithm for quantitatively characterizing material microstructure in three dimensions and in real time. This algorithm applies to most structural materials of interest to industry.
Cornell researchers have developed an automated system that uses machine learning, data analysis and human feedback to automatically verify statistical claims about the new coronavirus.
ResoluteAI, the Connect to Discover™ company, today announced the launch of Nebula, its enterprise search solution for scientific organizations. Nebula tags and categorizes users' content, connecting their proprietary information to ResoluteAI's platform of comprehensive scientific databases.
Activity from phony Twitter accounts established by the Russian Internet Research Agency between 2015 and 2017 may have contributed to politicizing Americans’ position on the nature and efficacy of vaccines, a health care topic which has not historically fallen along party lines, according to new research published in the American Journal of Public Health.
tellic, a technology startup based in New York, NY has been working for five years to develop an AI tool that surfaces actionable insights from biomedical research. Numerous biopharma currently use tellic graph as an AI-powered literature review tool to expedite their research.
Daily life during a pandemic means social distancing and finding new ways to remotely connect with friends, family and co-workers. And as we communicate online and by text, artificial intelligence could play a role in keeping our conversations on track, according to new Cornell University research.
The temptation for businesses to use artificial intelligence and other technology to improve performance, drive down labor costs, and better the bottom line is understandable. But before pursuing automation that could put the jobs of human employees at risk, it is important that business owners take careful stock of their operations.
A type of artificial intelligence called machine learning can help predict which patients will develop diabetes, according to an ENDO 2020 abstract that will be published in a special supplemental section of the Journal of the Endocrine Society.
Artificial intelligence that can “read” electronic radiology reports and flag patients with broken bones who are at risk of osteoporosis outperformed the traditional manual method of health care professionals reading X-ray reports, a new study finds. The results were accepted for presentation at ENDO 2020, the Endocrine Society’s annual meeting, and will be published in a special supplemental section of the Journal of the Endocrine Society.
An artificial intelligence tool accurately predicted which patients newly infected with the COVID-19 virus would go on to develop severe respiratory disease, a new study has found.
The U.S. Department of Energy’s Argonne National Laboratory Educational Programs and Outreach hosted the 2020 Illinois Regional Science Bowl Competition, where 15 different schools competed in trivia across a wide range of STEM topics.
Argonne scientists and engineers are looking toward AI — specifically, machine learning — to help us better understand the mechanics that govern nuclear reactors.
Can robots be effective tools in combating the COVID-19 pandemic? A group of leaders in the field of robotics say yes, and outline a number of examples in an editorial in the March 25 issue of Science Robotics. They say robots can be used for clinical care such as telemedicine and decontamination; logistics such as delivery and handling of contaminated waste; and reconnaissance such as monitoring compliance with voluntary quarantines.
Led by Eric Boerwinkle, PhD, and Momiao Xiong, PhD, The University of Texas Health Science Center at Houston (UTHealth) modeled the potential spread of COVID-19 based on whether the Greater Houston area began stringent interventions immediately or waited one week or two weeks. That data was presented Monday to city and county officials.
Scientists have developed a new artificial intelligence method that automates experiments by autonomously defining and conducting the next step of an experiment without input from human researchers. It works by creating a model that fits experimental data, then using that model as the starting point for continuously refining the model to fit with new data.
The Notre Dame project is an effort to combat the rise of coordinated social media campaigns to incite violence, sew discord and threaten the integrity of democratic elections.
Lawrence Livermore National Laboratory scientists are contributing to the global fight against COVID-19 by combining artificial intelligence/machine learning, bioinformatics and supercomputing to help discover candidates for new antibodies and pharmaceutical drugs to combat the disease.
Researchers have used artificial intelligence to detect Vietnam War-era bomb craters in Cambodia from satellite images – with the hope that it can help find unexploded bombs.
A method of predicting the coronavirus spread – pioneered and developed by Weizmann Institute scientists – may enable authorities to focus efforts on areas where an outbreak is anticipated and relieve measures taken in others. Several countries, including the U.S., are adopting the new method
Just released is the April edition of SLAS Technology featuring cover article, “CURATE.AI: Optimizing Personalized Medicine with Artificial Intelligence,” by Agata Blasiak, Ph.D., Jeffrey Khong, Ph.D., and Theodore Kee, Ph.D., (University of Singapore and The N.1 Institute for Health).
In a machine learning challenge dubbed the 2020 Large Hadron Collider Olympics, a team of cosmologists from Berkeley Lab developed a code that best identified a mock signal hidden in simulated particle-collision data.
Researchers will discuss how artificial intelligence and drones are being incorporated into health care when they share the latest emerging science during the Endocrine Society’s ENDO 2020 virtual news conferences March 30-31.
Unmanned aerial vehicles (UAV), commonly known as drones, are widely used in mapping, aerial photography, rescue operations, shipping, law enforcement, agriculture, among other things. Despite great potential for improving public safety, use of drones can also lead to very undesirable situations, such as privacy and safety violations, or property damage.
Research led by a Princeton University graduate student demonstrates that machine learning can predict and avoid damaging disruptions to fusion facilities.
Proteins are the building blocks of life and scientists have long studied how to improve them or design new ones. Traditionally, new proteins are created by mimicking existing proteins or manually editing their amino acids. This process is time-consuming, and it is difficult to predict the impact of changing an amino acid. In APL Bioengineering, researchers explore how to create new proteins by using machine learning to translate protein structures into musical scores, presenting an unusual way to translate physics concepts across domains.
Researchers at Missouri S&T are developing an airborne-biohazard system that could help screeners spot air travelers with lung diseases due to coronavirus and other viruses. Professors in electrical and computer engineering are using machine learning to build a robust system to alert authorities to airborne biohazards as travelers pass through TSA security checkpoints.
New Cornell research explains some of these functions through a computer algorithm inspired by the mammalian olfactory system. The algorithm both sheds light on how the brain works and, applied to a computer chip, rapidly and reliably learns patterns better than existing machine learning models.
Researchers from seven institutions team up to create a device combining artificial intelligence, bioelectronics and regenerative medicine for regrowing muscle tissue, especially after combat injuries.
Stanford University researchers created an inverse design codebase called SPINS that can help researchers explore different design methodologies to find fabricable optical and nanophotonic structures. In the journal Applied Physics Reviews, Logan Su and colleagues review inverse design’s potential for optical and nanophotonic structures, as well as present and explain how to use their own inverse design codebase.
A Cornell collaboration led by physicist Brad Ramshaw, the Dick & Dale Reis Johnson Assistant Professor in the College of Arts and Sciences, used a combination of ultrasound and machine learning to narrow the possible explanations for what happens to this quantum material when it enters this so-called “hidden order.”
A coronavirus app coupled with machine intelligence will soon enable an individual to get an at-home risk assessment based on how they feel and where they've been in about a minute, and direct those deemed at risk to the nearest definitive testing facility, investigators say.
An artificial intelligence (AI) device that has been fast-tracked for approval by the Food and Drug Administration may help identify newborns at risk for aggressive posterior retinopathy of prematurity (AP-ROP). AP-ROP is the most severe form of ROP and can be difficult to diagnose in time to save vision.
Artificial Intelligence (AI) is changing the world, with its own developments happening every day
DHS S&T is calling for submissions to the 2020 Biometric Technology Rally (Rally).
Rutgers engineers have created a tabletop device that combines a robot, artificial intelligence and near-infrared and ultrasound imaging to draw blood or insert catheters to deliver fluids and drugs. Their research results, published in the journal Nature Machine Intelligence, suggest that autonomous systems like the image-guided robotic device could outperform people on some complex medical tasks.
The advanced technology has the potential to change acute stroke treatment.
A new machine-learning computer model accurately predicts damaging radiation storms caused by the Van Allen belts two days prior to the storm, the most advanced notice to date, according to a new paper in the journal Space Weather.
Dr. Kang Zhang uses artificial intelligence (AI) to teach computers to create illustrations in the style of the famous masters: Jackson Pollock and his paint splatters or Joan Miró and his curved shapes and sharp lines. The process involves feeding computers examples of colors, abstract shapes and layouts so they can learn to produce their own versions of masterpieces.
ORNL's Story Tips: Antidote chasing, traffic control and automatic modeling, for March 2020
To ensure that the Indiana University Kelley School of Business continues to be responsive to the needs of a 21st-century global economy, the school's leadership announced that its Full-Time MBA Program will offer STEM-designated degrees in five disciplines. Beginning with those earning degrees this spring, MBAs with majors in accounting, business analytics, finance, marketing, and supply chain and operations will carry the extra designation of being Science, Technology, Engineering and Math certified.
Astrophysicists supported by the Department of Energy’s Office of Science are developing these guides in the form of computer models that rely on machine learning to examine the LSST data.
One of the most difficult problems to overcome in developing a quantum computer is finding a way to maintain the lifespan of information held in quantum bits, called qubits. Researchers at Fermilab and Argonne National Laboratory are working to determine whether devices used in particle accelerators can help solve the problem. The team will run simulations on high-performance computers that will enable them to predict the lifespan of information held within these qubits using smaller versions of these devices, taking us one step closer to the age of quantum computing.
The National Science Foundation has recognized Fabrizio Sergi, assistant professor of biomedical engineering at the University of Delaware, with its CAREER award to support fundamental research in motor control. His work is seeking to help those with movement disorders and identify robot-based interventions.
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