A team of Argonne scientists has leveraged artificial intelligence to train computers to keep up with the massive amounts of X-ray data taken at the Advanced Photon Source.
The U.S. Department of Energy has awarded $4.15 million to Argonne National Laboratory to support collaborations with industry aimed at commercializing promising energy technologies.
Researchers are the first to model COVID-19 completion versus cessation in clinical trials using machine learning algorithms and ensemble learning. They collected 4,441 COVID-19 trials from ClinicalTrials.gov to build a testbed with 693 dimensional features created to represent each clinical trial. These computational methods can predict whether a COVID-19 clinical trial will be completed or terminated, withdrawn or suspended. Stakeholders can leverage the predictions to plan resources, reduce costs, and minimize the time of the clinical study.
Prosthetics currently lack the sensation of “touch.” To enable a more natural feeling prosthetic hand interface, researchers are the first to incorporate stretchable tactile sensors using liquid metal and machine learning. This hierarchical multi-finger tactile sensation integration could provide a higher level of intelligence for artificial hands by improving control, providing haptic feedback and reconnecting amputees to a previously severed sense of touch.
Researchers at University of California San Diego School of Medicine describe a new approach that uses machine learning to hunt for disease targets and then predicts whether a drug is likely to receive FDA approval.
Department of Radiology Chair Elizabeth Morris, with the UC Davis Comprehensive Cancer Center, was awarded a Susan G. Komen® grant to develop artificial intelligence models to predict breast cancer risk at a more personalized level
Researchers at Argonne have used artificial intelligence to dramatically reduce the time it takes to process data coming from the Laser Interferometer Gravitational-Wave Observatory.
Researchers at Aalto University have harnessed the power of chatbots to help designers and developers develop new apps and allow end users to find information on the apps on their devices. The chatbot ‘Hey GUI’ can answer questions by showing images and screenshots of apps, or through simple text phrases.
The University of South Australia will lead a world-first study, using artificial intelligence, to map the risks of the most fatal reproductive cancer in women worldwide so it can be detected and treated earlier.
For most patients, the reasons for having a facelift are simple: to “turn back the clock” for a younger and more attractive appearance. Even during the pandemic year 2020, more than 234,000 patients underwent facelift surgery, according to American Society of Plastic Surgeons (ASPS) statistics.
Finland’s Aalto University begins collaboration with Swedish universities in the Wallenberg Artificial Intelligence, Autonomous Systems and Software Program (WASP)
DHS SBIR Program recently awarded funding to two small businesses to develop non-contact, inexpensive machine learning training and classification technologies.
PNNL researchers are expanding PNNL’s operational Rapid Analytics for Disaster Response (RADR) image analytics and modeling suite to predict the path of fires, floods and other natural disasters, giving first responders an upper hand. The suite utilizes a combination of image-capturing technology (satellite, airborne, and drone images), artificial intelligence, and cloud computing, to not only assess damage but predict it as well.
Machine learning can improve the ability of scientists to optimize the components of experiments on spherical tokamaks that heat and shape the magnetically confined plasma that fuels fusion reactions.
Advanced Artificial Intelligence System Provides Real-Time Analysis of the Knee in Motion for Improved Diagnosis and Treatment Planning
In the not-so-distant future, artificial intelligence and machine learning tasks will be carried out among connected devices through wireless networks, dramatically enhancing the capabilities of future smartphones, tablets, and sensors, and achieving what’s known as distributed intelligence. As technology stands right now, however, machine learning algorithms are not efficient enough to be run over wireless networks and wireless networks are not yet ready to transmit this type of intelligence.
PNNL researchers used natural language processing and deep learning techniques to reveal how and why different types of misinformation and disinformation spread across social platforms. Applied to COVID-19, the team found that misinformation intended to influence politics and incite fear spreads fastest.
In the future, health care delivery systems and personnel will rely more on automation and artificial intelligence. It is likely that there will be a paradigm shift in the nursing field towards a more targeted, technologically advanced and data-oriented health care delivery system.
Machine learning techniques are accelerating the development of stronger alloys for power plants, which will yield efficiency, cost, and decarbonization benefits.
Artificial intelligence (AI) may offer a way to accurately determine that a person is not infected with COVID-19. An international retrospective study finds that infection with SARS-CoV-2, the virus that causes COVID-19, creates subtle electrical changes in the heart. An AI-enhanced EKG can detect these changes and potentially be used as a rapid, reliable COVID-19 screening test to rule out COVID-19 infection.
UW researchers have developed a deep learning method that can produce a seamlessly looping, realistic looking video from a single photo.
A new Cleveland Clinic-led study has identified mechanisms by which COVID-19 can lead to Alzheimer’s disease-like dementia. The findings, published in Alzheimer’s Research & Therapy, indicate an overlap between COVID-19 and brain changes common in Alzheimer’s, and may help inform risk management and therapeutic strategies for COVID-19-associated cognitive impairment.
An ORNL-led team comprising researchers from multiple DOE national laboratories is using artificial intelligence and computational screening techniques – in combination with experimental validation – to identify and design five promising drug therapy approaches to target the SARS-CoV-2 virus.
Today, the U.S. Department of Energy (DOE) announced $1 million for collaborations in privacy-preserving artificial intelligence research. The aim of this funding is to bring together researchers from the DOE National Laboratories and the National Institutes of Health (NIH) to jointly develop new flagship datasets and privacy-preserving methods and algorithms to improve healthcare.
Researchers at the Finnish Center for Artificial Intelligence have developed a machine learning-based method that produces synthetic data, making it possible for researchers to share even sensitive data with one other without privacy concerns.
DHS S&T partnered with the Johns Hopkins University Applied Physics Laboratory and Think-A-Move to develop Automated Speech Recognition technology.
The impact of deploying Artificial Intelligence (AI) for radiation cancer therapy in a real-world clinical setting has been tested by Princess Margaret researchers in a unique study involving physicians and their patients.
A team of NIH microscopists and computer scientists used a type of artificial intelligence called a neural network to obtain clearer pictures of cells at work even with extremely low, cell-friendly light levels.
University of Washington researchers discovered that AI models ignored clinically significant indicators on X-rays and relied instead on characteristics such as text markers or patient positioning that were specific to each dataset to predict whether someone had COVID-19.
A doctoral student’s research at The University of Alabama in Huntsville (UAH) to improve the application of artificial intelligence to better understand online user product preferences won the best research paper award at the recent virtual Association for Computing Machinery (ACM) Southeast Conference.
Artificial intelligence is being called “the next generation of the way we do science.” At Argonne, researchers are leveraging the lab’s state-of-the-art-facilities and unparalleled expertise to shape the very future of science.
Computer scientists at the University of Illinois Chicago are developing a computational artificial intelligence system they hope will serve as a decision support tool for doctors prescribing treatment for head and neck cancer. The work is supported by a $2.8 million grant from the National Institutes of Health.
You might be older ― or younger ― than you think. A new study found that differences between a person’s age in years and his or her biological age, as predicted by an artificial intelligence (AI)-enabled EKG, can provide measurable insights into health and longevity.
We Are AI is a 5-week course to introduce people to the basics of AI and empower individuals to engage with how AI is used and governed. No math, programming skills, or existing understanding of AI are required.
Cornell University is partnering in a $36 million grant from the Toyota Research Institute (TRI) for its Accelerated Materials Design and Discovery (AMDD) collaborative university research program, which seeks to use artificial intelligence to discover new materials that could help achieve emissions-free driving.
Machine learns to categorize pottery comparable to expert archaeologists, matches designs among thousands of broken pieces
In a collaboration between Pacific Northwest National Laboratory and the University of Washington’s Urban Freight Lab, a prototype webapp has been developed that combines smart sensors and machine learning to predict parking space availability. The prototype is ready for initial testing to help commercial delivery drivers find open spaces without expending fuel and losing time and patience.
For AI to continue to transform cancer diagnoses, researchers will have to prove that the success of their machine-learning tools can be reproduced from site to site and among different patient populations. Biomedical engineering researchers at Case Western Reserve University say they doing just that. They say they have demonstrated that their novel algorithms for distinguishing between benign and malignant lung cancer nodules on CT scan images from one site can now be successfully reproduced with patients from other sites and locations.
Peri-implantitis, a condition where tissue and bone around dental implants becomes infected, besets roughly one-quarter of dental implant patients, and currently there’s no reliable way to assess how patients will respond to treatment of this condition.
Argonne scientists across several disciplines have combined forces to create a new process for testing and predicting the effects of high temperatures on refractory oxides.
To make drugs and their development safer for children, researchers at Aalto University and the pharmaceutical company Novartis have developed a method to help determine safe drug doses more quickly. The new organ maturation model is more data-driven and consequently less prone to bias.
Argonne is helping U.S. companies solve pressing manufacturing challenges through an innovative program that provides access to Argonne’s world-class computing resources and technical expertise.
The Department of Energy has awarded Argonne and partners $2 million to develop an artificial intelligence-assisted system for energy, nutrient and freshwater recovery from municipal wastewater.
At the Department of Energy’s Oak Ridge National Laboratory, scientists use artificial intelligence, or AI, to accelerate the discovery and development of materials for energy and information technologies.
The Department of Energy’s Oak Ridge National Laboratory has licensed its award-winning artificial intelligence software system, the Multinode Evolutionary Neural Networks for Deep Learning, to General Motors for use in vehicle technology and design.
The American College of Radiology® (ACR®) Data Science Institute® (DSI) and the Cancer Imaging Archive (TCIA), funded by the National Cancer Institute (NCI), have teamed up to connect use cases and datasets to speed medical imaging artificial intelligence (AI) development.
Argonne engineer Meltem Urgun-Demirtas leads the Bioprocesses and Reactive Separations group at Argonne, where she brings more than 20 years of diverse experience in waste and water treatment, biofuels production and materials synthesis for energy and environmental applications. Working with…
The Graduate School of Biomedical Sciences at the Icahn School of Medicine at Mount Sinai will offer a new PhD concentration in Artificial Intelligence and Emerging Technologies in Medicine (AIET) as part of its PhD in Biomedical Sciences program. Hayit Greenspan, PhD and Alan C. Seifert, PhD are the newly appointed AIET Co-Directors. Application will be open from late August through December 1, 2021 for enrollment in the fall of 2022.
Stepping into their superhero gear, Argonne scientists are using science and the world’s best technology to combat some of Earth’s toughest foes, from pollution to climate change.
Spiking neural networks (SNNs) closely replicate the structure of the human brain, making them an important step on the road to developing artificial intelligence. Researchers recently advanced a key technique for training SNNs using an evolutionary approach. This approach involves recognizing and making use of the different strengths of individual elements of the SNN.