New York University physicists have created new techniques that deploy machine learning as a means to significantly improve data analysis for the Large Hadron Collider, the world’s most powerful particle accelerator.
To explore extreme environments, machines need to think like humans. Engineers are working to solve fundamental scientific problems to make intelligent control systems possible.
NYU School of Medicine's Center for Advanced Imaging Innovation and Research, supported by NIBIB, will collaborate with Facebook Artificial Intelligence Research on an imaging project, called fastMRI, that will use AI to make MRI scans up to 10 times faster.
Researchers view cells for hearing in 3D using virtual reality
Cornell University’s Elephant Listening Project tracks African forest elephants with acoustic sensors, but the forests are so remote and the sound files so huge it takes months to collect and analyze the data – too long to rescue the animals from poachers or other threats. Now scientists can learn critical information about the elephants’ habits and patterns in a fifth of the time. A startup, Conservation Metrics, developed a tool that uses artificial intelligence to distinguish the low-frequency, long-duration elephant calls from other rainforest sounds.
A translational research team led by the National University of Singapore (NUS) has harnessed CURATE.AI, a powerful artificial intelligence (AI) platform, to successfully treat a patient with advanced cancer, completely halting disease progression. This new development represents a big step forward in personalised medicine.
Piece describes selection of deep learning system for predicting fusion disruptions as one of 10 Aurora Early Science exascale projects.
On August 15, a cohort of undergraduate students who had participated in the Summer Undergraduate Laboratory Internship and Community College Internship programs presented the results of the plasma physics work they had completed since their internships began on June 11.
With more businesses using artificial intelligence to engage with consumers, the industry is working to make those interactions more human-like. An Iowa State researcher is contributing to that effort by improving how machines, such as smartphones and computers, understand and generate language.
Collaboration powers machine learning software that performs data analytics on petabyte-sized data sets in series of successful test runs.
The American College of Radiology’s Neiman Institute and the Georgia Institute of Technology announced a new five-year, $3 million research partnership to establish the Health Economics and Analytics Lab (HEAL) within Georgia Tech’s Ivan Allen College of Liberal Arts.
The study’s findings lay the framework for applying deep learning and computer vision techniques to radiological imaging.
A multidisciplinary team of researchers from the National University of Singapore (NUS) has developed an artificial intelligence (AI) technology platform that could potentially change the way drug combinations are being designed, hence enabling doctors to determine the most effective drug combination for a patient quickly
Papers on nephrotoxicity, nanomaterial genotoxicity, machine learning; arsenic and telomere length in children; iPSC-derived cardiomyoctes for drug safety studies; and asthma, air pollution, and immunity featured in latest issue of Toxicological Sciences
Through a recently awarded Penn State Teaching and Learning with Technology Fellowship, Alan Wagner, assistant professor of aerospace engineering at Penn State, will develop an experimental framework, using immersive social spaces, to investigate how social, artificially intelligent robots in higher education can foster and enforce ethical behavior and academic integrity with students.
Professor William Yeoh is designing algorithms to run the smart homes of the future – and he's making sure they won't bother us too much.
A new study using machine learning has identified brain-based dimensions of mental health disorders, an advance towards much-needed biomarkers to more accurately diagnose and treat patients.
If you're looking for new health and fitness story ideas, here are some highlights from ACSM programs and recently released research in ACSM’s flagship journal, Medicine & Science in Sports & Exercise®. The American College of Sports Medicine is the largest sports medicine and exercise science organization in the world.
UCI artificial intelligence center will develop, apply deep learning neural networks to diagnostics, disease prediction and therapy planning. Initial research includes developing a system with 97%+ accuracy in near real-time detection of brain bleeds on NCCT. System to be implemented in UCI’s comprehensive stroke program.
It’s often been said that the eyes are the window to the soul, revealing what we think and how we feel. Now, new research reveals that your eyes may also be an indicator of your personality type, simply by the way they move.
To prevent bias in hiring and other contexts, researchers present an algorithm that imposes a fairness constraint on machine learning.
A team of Florida State University researchers is using artificial intelligence to identify which among hundreds of thousands of hypothetical crystal structures can result in the prediction of new chemical compounds.
JENOPTIK Optical Systems, LLC collaborated with Google on microscopy technology to assist pathologists in detecting cancer with deep learning
The American College of Radiology Data Science InstituteTM (ACR DSI) is a co-sponsor for the National Institute of Biomedical Imaging and Bioengineering (NIBIB)’s Workshop on Artificial Intelligence (AI) in Medical Imaging. The two-day workshop aims to clarify the needs in foundational and translational research for machine learning in medical imaging.
A new initiative kicks off today to evaluate the use of artificial intelligence (AI) and situational awareness technologies during critical incidents. The effort is a joint partnership between DHS S&T and Canada’s Department of National Defence.
The American College of Radiology Data Science Institute (ACR DSI) began releasing its first use cases in the TOUCH-AI library to industry for comment this month, to generate feedback prior to the projected release of the use cases in the fall of 2018.
A research team with funding from the National Institute of Biomedical Imaging and Bioengineering has developed an advanced computing technique for rapidly and cost effectively improving the quality of biomedical imaging. The technology, called AUTOMAP finds the best computational strategies to produce clear, accurate images for various types of medical scans.
Want to be a good team player? Take a break. It may improve not only your own performance but the chances of your team winning overall, says a new study by a team of USC computer scientists.
Researchers from the Johns Hopkins University Applied Physics Laboratory (APL) in Laurel, Maryland, and collaborators at the Johns Hopkins School of Medicine, have developed image analysis and machine learning tools to detect age-related macular degeneration, and report in Nature Medicine that such tools can be applied to other image-based medical diagnoses.
The US Department of Energy’s Oak Ridge National Laboratory is once again officially home to the fastest supercomputer in the world, according to the TOP500 List, a semiannual ranking of the world’s fastest computing systems.
Four scientists at the Department of Energy’s SLAC National Accelerator Laboratory will receive Early Career Research Program awards for research that’s developing new ways to study fundamental particles with machine learning and study nanoscale objects and quantum materials with powerful X-ray laser beams.
Scientists at Pacific Northwest National Laboratory are exploring deep learning to interpret data related to national security, the environment, the cosmos, and breast cancer. In one project a deep neural network is interpreting data about nuclear events as well as – sometimes better than – today’s best automated methods or human experts.
In an effort to reduce errors in the analyses of diagnostic images by health professionals, a team of researchers from Oak Ridge National Laboratory has improved understanding of the cognitive processes involved in image interpretation, work that has enormous potential to improve health outcomes for the hundreds of thousands of American women affected by breast cancer each year. The ORNL-led team found that analyses of mammograms by radiologists were significantly influenced by context bias, or the radiologist’s previous diagnostic experiences.
Researchers at Berkeley Lab are currently developing a web-based search engine for scientific data, called Science Search. The team is also building innovative machine learning tools to pull contextual information from scientific datasets and automatically generate missing metadata tags for each raw and simulated data files. As a proof-of-concept, the team is working with staff at the Molecular Foundry, to demonstrate the concepts of Science Search on the images captured by the facility's instruments.
The concept of non-human beings endowed with intelligence dates back to at least Homer in the late eighth or early seventh century B.C. As society has developed and our ability to tell stories enhanced by technology, the idea of intelligent machines has captured the minds of societies across the globe.
A team of ASU students built an AI drone to detect wildfires before they become catastrophic. The students will compete for a $100,000 prize in an international Microsoft pitch competition this summer.
a team led by researchers at UC San Diego’s Department of Chemistry and Biochemistry and the San Diego Supercomputer Center (SDSC), has used machine learning techniques to develop models for simulations of water with “unprecedented accuracy.”
RNA sequencing and machine learning applied to develop new asthma biomarker
Scientists have developed an algorithm that predicts potentially dangerous low blood pressure, or hypotension, that can occur during surgery. The algorithm identifies hypotension 15 minutes before it occurs in 84 percent of cases, the researchers report in a new study published in the Online First edition of Anesthesiology.
The U.S. Department of Energy’s Oak Ridge National Laboratory today unveiled Summit as the world’s most powerful and smartest scientific supercomputer.
Machine learning using real-time symptom reports can accurately detect lymphedema, a distressing side effect of breast cancer treatment that is more easily treated when identified early, finds a new study led by NYU Rory Meyers College of Nursing and published in the journal mHealth.
It takes an “A” team to make headway against glioblastoma, a highly aggressive type of brain cancer. Glioblastoma is the most common type of malignant brain tumor in adults. In addition to the caliber of the researchers involved, in this case “A” also stands for atlas. A key member of the team, Jill S. Barnholtz-Sloan, PhD, Sally S. Morley Designated Professor in Brain Tumor Research at Case Western Reserve University School of Medicine, and approximately 80 other internationally renowned neurologists, bioinformaticians, and pathologists from the United States and India recently published details of the Ivy Glioblastoma Atlas in Science.
Premenopausal women with hormone receptor-positive, HER2-negative breast cancer and a high risk of recurrence who are treated with an aromatase inhibitor plus ovarian function suppression may gain 10 to 15 percent improvement in freedom from distant recurrence at eight years, according to a new clinical trial analysis reported at the annual meeting of the American Society of Clinical Oncology.
The new MTSU Data Science Institute officially launched in mid-May with a mission to promote funded interdisciplinary research and develop public and private collaborations around the emerging field of “big data.”
Artificial Intelligence (AI) will be deployed against Mount Sinai’s massive patient data warehouse biorepository and to innovate more accurate disease detection and management for introduction in 2019
The race is on for companies to present their driverless cars to the public, but recent collisions involving autonomous vehicles developed by Uber Technologies Inc. and Tesla Inc. have led consumers to questions whether these vehicles can alleviate traffic issues and increase safety. A new study published in Risk Analysis examined the question “How safe is safe enough for self-driving vehicles (SDVs)?”
In an effort to build the next generation of machine-learning methods to support its needs, the Air Force Office of Scientific Research and the Air Force Research Laboratory have awarded $5 million to establish a university center of excellence devoted to efficient and robust machine learning at the University of Wisconsin–Madison.
ISPOR, the professional society for health economics and outcomes research, held a session, “Is Artificial Intelligence the Next Big Thing in Healthcare Decision Making?”, at ISPOR 2018 in Baltimore, MD, USA.
Cornell University has teamed with the University of Bologna to establish the Cornell-Bologna Center for Vehicle Intelligence, a partnership that merges world-class research with some of the world’s most powerful and elegant automobiles.
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