AI-driven dynamic face mask adapts to exercise, pollution levels

Researchers reporting in ACS Nano have developed a dynamic respirator that modulates its pore size in response to changing conditions, such as exercise or air pollution levels, allowing the wearer to breathe easier when the highest levels of filtration are not required.

Researchers predict viewer interest, not just attention, in public screen content

We are constantly surrounded by screens that offer us information on the weather, current events or the latest offers from the corner shop. Yet most displays are updated manually, if at all. Researchers at Aalto University and the Finnish Center for Artificial Intelligence FCAI have developed a new, simpler way to choose and arrange public display content so that it really catches people’s attention.

Novel Insights on COVID-19 Vaccines and Virus Evolution, Artificial Intelligence in the Clinic, Miniaturization of Diagnostic Platforms, and Much More to Be Explored at the 2021 AACC Annual Scientific Meeting & Clinical Lab Expo

At the 2021 AACC Annual Scientific Meeting & Clinical Lab Expo, laboratory medicine experts will present the cutting-edge research and technology that is revolutionizing clinical testing and patient care.

Preparing for exascale: Argonne’s Aurora supercomputer to drive brain map construction

Argonne researchers are mapping the complex tangle of the brain’s connections — a connectome — by developing applications that will find their stride in the advent of exascale computing.

New machine learning method to analyze complex scientific data of proteins

Scientists have developed a method using machine learning to better analyze data from a powerful scientific tool: nuclear magnetic resonance (NMR). One way NMR data can be used is to understand proteins and chemical reactions in the human body. NMR is closely related to magnetic resonance imaging (MRI) for medical diagnosis.

Department of Energy Invests $1 Million in Artificial Intelligence Research for Privacy-Sensitive Datasets

The U.S. Department of Energy (DOE) announced $1 million for a one-year collaborative research project to develop artificial intelligence (AI) and machine learning (ML) algorithms for biomedical, personal healthcare, or other privacy-sensitive datasets.

Peachy Robot: A Glimpse into the Peach Orchard of the Future

Researchers are developing a robot that utilizes deep learning to automate certain aspects of the peach cultivation process, which could be a boon for many Georgia peach farms grappling with a shortage of workers. The self-navigating robot uses an embedded 3D camera to determine which trees need to be pruned or thinned, and removes the branches or peaches using a claw-like device attached to its arm.

Department of Energy Invests $16 Million in Data-Intensive Scientific Machine Learning Research and Analysis

The U.S. Department of Energy (DOE) announced $16 million for five collaborative research projects to develop artificial intelligence (AI) and machine learning (ML) algorithms for enabling scientific insights and discoveries from data generated by computational simulations, experiments, and observations.

‘Molecular Twin’ Initiative Will Help Advance Precision Cancer Treatment

Cedars-Sinai Cancer and Tempus, a leader in artificial intelligence and precision medicine, are harnessing the power of big data and AI to design personalized cancer treatment options by creating virtual replicas of patients’ DNA, RNA, protein and other information to help identify the most effective approach to each individual’s disease.

Unbound Medicine Launches Upgrade to Study System Using Artificial Intelligence

Unbound Medicine announced an upgrade to Grasp, their personal mobile study system. This latest version utilizes Unbound Intelligence, exclusive artificial intelligence and machine learning tools developed to help clinicians discover and fill knowledge gaps, as well as keep up to date with research.

Do Passengers Want Self-driving Cars to Behave More or Less Like Them?

Researchers asked participants about their personal driving behaviors such as speed, changing lanes, accelerating and decelerating and passing other vehicles. They also asked them the same questions about their expectations of a self-driving car performing these very same tasks. The objective of the study was to examine trust and distrust to see if there is a relationship between an individual’s driving behaviors and how they expect a self-driving car to behave.

U.S. Department of Energy’s Argonne National Laboratory and Hewlett Packard Enterprise prepare for exascale era with new testbed supercomputer

Argonne and HPE unveiled a new testbed supercomputer that will enable scientists and developers to test and optimize software codes and applications for the forthcoming exascale supercomputer, Aurora.

Baby detector software embedded in digital camera rivals ECG

Facial recognition is now common in adults, but University of South Australia researchers have developed software that can reliably detect a premature baby’s face in an incubator and remotely monitor its heart and breathing rates, rivalling ECG machines and even outperforming them. This is the first step in using non-contact monitoring in neonatal wards, avoiding skin tearing and potential infections from adhesive pads.x

Artificial Intelligence aids in discovery of new prognostic biomarkers for breast cancer

Scientists at Case Western Reserve University have used Artificial Intelligence (AI) to identify new biomarkers for breast cancer that can predict whether the cancer will return after treatment—and which can be identified from routinely acquired tissue biopsy samples of early-stage breast cancer.

Gaming the Research: Reinforcement Learning Changing Data Evaluation Challenges

Advances in artificial intelligence, specifically reinforcement learning, are proving beneficial to accelerating the pace of data-intensive challenges. The methods used by researchers with RL are techniques often used in video games, and by applying gamification to scientific processes, RL agents can learn as they are used in experiments, in effect, leveling up their rates of discovery as they work. Researchers are using trained RL agents at NSLS-II to accelerate the analysis of data-heavy measurements.

San Diego Supercomputer Center Plays a Role in NSF’s New ICICLE Institute

The AI Institute for Intelligent Cyberinfrastructure with Computational Learning in the Environment, or ICICLE, will focus on next-generation intelligent cyberinfrastructure that makes using AI as easy as plugging an appliance into an electrical outlet.

UW to lead new NSF institute for using artificial intelligence to understand dynamic systems

The University of Washington will lead a new artificial intelligence research institute that will focus on fundamental AI and machine learning theory, algorithms and applications for real-time learning and control of complex dynamic systems, which describe chaotic situations where conditions are constantly shifting and hard to predict.

Case Western Reserve data scientists among national Artificial Intelligence initiative

Vipin Chaudhary, chair of computer and data sciences at Case Western Reserve, is co-primary investigator on the new grant announced today by the U.S. National Science Foundation (NSF). He will collaborate with Ohio State computer science and engineering professor Dhabaleshwar Panda, the primary investigator on the project, which will focus on building AI systems for agricultural and wildlife management systems.

Automatically Steering Experiments Toward Scientific Discovery

Scientists at Brookhaven and Lawrence Berkeley National Laboratories have been developing an automated experimental setup of data collection, analysis, and decision making.

New Tool Predicts Sudden Death in Inflammatory Heart Disease

Johns Hopkins University scientists have developed a new tool for predicting which patients suffering from a complex inflammatory heart disease are at risk of sudden cardiac arrest. Published in Science Advances, their method is the first to combine models of patients’ hearts built from multiple images with the power of machine learning.

Now in 3D: Deep learning techniques help visualize X-ray data in three dimensions

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.

Department of Energy awards $4.15 million to Argonne to support collaborations with industry

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.

Novel Method Predicts if COVID-19 Clinical Trials Will Fail or Succeed

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.

Liquid Metal Sensors and AI Could Help Prosthetic Hands to ‘Feel’

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.