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UrduA new advanced artificial intelligence (AI) system has shown world-leading accuracy and speed in identifying protein patterns within individual cells.
Tag: Machine Learning
Cedars-Sinai Establishes Center for Artificial Intelligence Research and Education
The Cedars-Sinai Department of Computational Biomedicine recently sharpened its focus on advancing artificial intelligence and machine learning by establishing the Center for Artificial Intelligence Research and Education.
What really killed COVID-19 patients: it wasn’t a cytokine storm
Secondary bacterial infection of the lung (pneumonia) was extremely common in patients with COVID-19, affecting almost half the patients who required support from mechanical ventilation.
Scientists develop pioneering artificial intelligence method to fight urban air pollution
99% of the world’s population breathes air that exceeds the limits recommended by the World Health Organization (WHO). This scenario is exacerbated in urban areas where more than 50% of the world’s population is concentrated.
AI-collected data could compromise childhood sleep disorder diagnoses
A dearth of paediatric data collected using artificial intelligence (AI) tools could compromise the understanding of early sleep patterns.
Argonne’s self-driving lab accelerates the discovery process for materials with multiple applications
Researchers have a new scientific tool called Polybot, combining the power of artificial intelligence with robotics. This autonomous discovery lab is leading the way in transforming scientific research on sustainable and bio-inspired microelectronics.
Study shows how machine learning can identify social grooming behavior from acceleration signals in wild baboons
Scientists from Swansea University and the University of Cape Town have tracked social grooming behaviour in wild baboons using collar-mounted accelerometers.
Finnish population-based study: Vulnerable groups were the least likely to uptake COVID-19 vaccination
A large-scale registry study in Finland has identified several factors associated with uptake of the first dose of COVID-19 vaccination. In particular, persons with low or no labor income and persons with mental health or substance abuse issues were less likely to vaccinate.
Model that uses machine learning methods and patient data at hospital arrival predicts strokes more accurately than current system
Stroke is among the most dangerous and commonly misdiagnosed medical conditions. Black and Hispanic people, women, older people on Medicare, and people in rural areas are less likely to be diagnosed in time for treatment to be effective.
No magic number for time it takes to form habits
The study is the first to use machine learning tools to study habit formation. The researchers employed machine learning to analyze large data sets of tens of thousands of people who were either swiping their badges to enter their gym or washing their hands during hospital shifts.
Warming climate will affect streamflow in the northeast
A new Dartmouth study provides insight into how changes in precipitation and temperature due to global warming affect streamflow and flooding in the Northeast. The findings are published in the Journal of the American Water Resources Association.
Machine-learning technique identifies people who would benefit most from treatment to reduce future cardiovascular disease risk
New UCLA research suggests that a novel machine-learning technique known as “causal forest” was about five times more efficient than the current clinical practice of treating patients with high blood pressure.
Bright lights, big data: how Argonne is bringing supercomputing and X-rays together for scientific breakthroughs
Argonne’s newest supercomputer, Polaris, is up and running, and scientists using the Advanced Photon Source are already seeing faster data analysis. While the combination is paying dividends now, it points toward an upgraded APS and an even better supercomputer called Aurora.
Científicos logran mejorar la nitidez de la primera imagen de un agujero negro
Un equipo de científicos, que incluyó a un astrónomo de NOIRLab de NSF, desarrolló una nueva técnica de aprendizaje automático (machine-learning) para mejorar la definición y la nitidez de imágenes de interferometría de radio. Para demostrar el poder de su nueva técnica, a la que llamaron PRIMO, el equipo creó una nueva versión, en alta definición, de la icónica imagen captada por el Telescopio Event Horizon del agujero negro supermasivo ubicado al centro de Messier 87, una galaxia elíptica gigante localizada a unos 55 millones de años luz de la Tierra.
A Sharper Look at the First Image of a Black Hole
A team of researchers, including an astronomer with NSF’s NOIRLab, has developed a new machine-learning technique to enhance the fidelity and sharpness of radio interferometry images. To demonstrate the power of their new approach, which is called PRIMO, the team created a new, high-fidelity version of the iconic Event Horizon Telescope’s image of the supermassive black hole at the center of Messier 87, a giant elliptical galaxy located 55 million light-years from Earth.
Decoding Insomnia: Machine learning model predicts sleep disorders from patient records
A machine learning model can effectively predict a patient’s risk for a sleep disorder using demographic and lifestyle data, physical exam results and laboratory values, according to a new study published this week in the open-access journal PLOS ONE.
It’s all in the wrist: energy-efficient robot hand learns how not to drop the ball
Researchers have designed a low-cost, energy-efficient robotic hand that can grasp a range of objects – and not drop them – using just the movement of its wrist and the feeling in its ‘skin’.
New “AI scientist” combines theory and data to discover scientific equations
In 1918, the American chemist Irving Langmuir published a paper examining the behavior of gas molecules sticking to a solid surface.
Detecting stress in the office from how people type and click
In Switzerland, one in three employees suffers from workplace stress. Those affected often don’t realise that their physical and mental resources are dwindling until it’s too late. This makes it all the more important to identify work-related stress as early as possible where it arises: in the workplace.
Two Early-Career Researchers Capture 2022 JCP Emerging Investigator Awards
The Journal of Chemical Physics is pleased to announce Bingqing Cheng and Katrin Erath-Dulitz as the 2022 winners of the JCP Best Paper by an Emerging Investigator Awards. Cheng was selected for research that exploits machine learning to understand and predict material properties and Erath-Dulitz was recognized for developing a method that controllably prepares chemical reactions to explore their quantum nature. Each winner will receive a $2,000 honorarium and is invited to write a perspective article for JCP.
Five Ways QSA is Advancing Quantum Computing
The Quantum Systems Accelerator has issued an impact report that details progress made since the center launched in 2020. Highlights include a record-setting quantum sensor that could be used to hunt dark matter, a machine learning algorithm to correct qubit errors in real time, and the first observation of several exotic states of matter using a 256-atom quantum device.
Four different autism subtypes identified in brain study
People with autism spectrum disorder can be classified into four distinct subtypes based on their brain activity and behavior, according to a study from Weill Cornell Medicine investigators.
Optimizing sepsis treatment timing with a machine learning model
A new machine learning model that estimates optimal treatment timing for sepsis could pave the way for support tools that help physicians personalize treatment decisions at the patient bedside, researchers say.
Smart watches could predict higher risk of heart failure
The peer-reviewed study, published in The European Heart Journal – Digital Health, looked at data from 83,000 people who had undergone a 15-second electrocardiogram (ECG) comparable to the kind carried out using smart watches and phone devices.
Prototype taps into the sensing capabilities of any smartphone to screen for prediabetes
Researchers at the University of Washington have developed GlucoScreen, a system that could enable people to self-screen for prediabetes.
Machine learning models rank predictive risks for Alzheimer’s disease
Once adults reach age 65, the threshold age for the onset of Alzheimer’s disease, the extent of their genetic risk may outweigh age as a predictor of whether they will develop the fatal brain disorder, a new study suggests.
AI shows the need for healthier diets in long-term care homes
A detailed analysis of consumed food showed there is a need to improve diets in long-term care (LTC) homes to make them healthier for residents.
Making immunizations more effective
In addition to an antigen, many vaccines also contain substances, called adjuvants, which stimulate the immune system. By using computer-aided molecular design and machine learning, a Chinese research team has now developed two novel broad-spectrum adjuvants that can significantly amplify the immune response to vaccines.
ORNL malware ‘vaccine’ generator licensed for Evasive.ai platform
A technology developed at Oak Ridge National Laboratory and used by the U.S. Naval Information Warfare Systems Command to test the capabilities of commercial security tools has been licensed to cybersecurity firm Penguin Mustache to create its Evasive.ai platform.
Q&A: How to make computing more sustainable
SLAC researcher Sadasivan Shankar talks about a new environmental effort starting at the lab – building a roadmap that will help researchers improve the energy efficiency of computing, from devices like cellphones to artificial intelligence.
Could AI-powered object recognition technology help solve wheat disease?
A new University of Illinois project is using advanced object recognition technology to keep toxin-contaminated wheat kernels out of the food supply and to help researchers make wheat more resistant to fusarium head blight, or scab disease, the crop’s top nemesis.
Machine learning helps researchers separate compostable from conventional plastic waste with ‘very high’ accuracy
Disposable plastics are everywhere: Food containers, coffee cups, plastic bags. Some of these plastics, called compostable plastics, can be engineered to biodegrade under controlled conditions.
Neural network learns how to identify chromatid cohesion defects
Scientists from Tokyo Metropolitan University have used machine learning to automate the identification of defects in sister chromatid cohesion.
JMIR Medical Education Launches Special Issue on the Use of ChatGPT in Medical Education, After New Study Finds ChatGPT Passes the United States Medical Licensing Examination
A study published on February 8, 2023, in JMIR Medical Education, a leading open access journal on digital medical education, evaluated the potential of ChatGPT, a natural language processing model, as a medical education tool. The study found that ChatGPT reaches the equivalent of a passing score for a third-year medical student.
Expert Available on Artificial Intelligence, ChatGPT
Rensselaer Polytechnic Institute’s James Hendler is the Director of the Future of Computing Institute; Tetherless World Professor of Computer, Web and Cognitive Sciences; and Director of the RPI-IBM Artificial Intelligence Research Collaboration. “In a nutshell, ChatGPT creates something not dissimilar…
Rutgers Researchers Use Artificial Intelligence to Predict Cardiovascular Disease
According to a new study from Rutgers Institute for Health, researchers may be able to predict cardiovascular disease in patients by using artificial intelligence to examine the genes in their DNA.
Hackers could try to take over a military aircraft; can a cyber shuffle stop them?
A cybersecurity technique that shuffles network addresses like a blackjack dealer shuffles playing cards could effectively befuddle hackers gambling for control of a military jet, commercial airliner or spacecraft, according to new research.
Digital markers near-perfect for predicting dementia
Using ensemble learning techniques and longitudinal data from a large naturalistic driving study, researchers at Columbia University’s Mailman School of Public Health, Fu Foundation School of Engineering and Applied Science, and Vagelos College of Physicians and Surgeons have developed a novel, interpretable and highly accurate algorithm for predicting mild cognitive impairment and dementia in older drivers.
UC Irvine researchers create E. coli-based water monitoring technology
Irvine, Calif., Feb. 23, 2023 – People often associate Escherichia coli with contaminated food, but E. coli has long been a workhorse in biotechnology. Scientists at the University of California, Irvine have demonstrated that the bacterium has further value as part of a system to detect heavy metal contamination in water. E.
Argonne training program introduces AI for science to a new crowd
The Intro to AI-Driven Science on Supercomputers training series gives students hands-on experience using the Lab’s high performance computing resources.
Research Team Creates Statistical Model to Predict Covid-19 Resistance
Researchers from Johns Hopkins Medicine and The Johns Hopkins University have created and preliminarily tested what they believe may be one of the first models for predicting who has the highest probability of being resistant to COVID-19 in spite of exposure to SARS-CoV-2, the virus that causes it.
Machine Learning Takes Hold in Nuclear Physics
In the past several years, nuclear physics researchers have initiated a flurry of machine learning projects and published many papers on the subject. A new survey by 18 authors from 11 institutions summarizes this work to provide an educational resource and a roadmap for future endeavors in the field.
Internships help students create prototypes for career success
Argonne’s Rapid Prototyping Laboratory is a testing ground for new ideas and new careers in autonomous discovery. Undergraduate and graduate student interns are learning how to automate lab work using robotics and artificial intelligence.
How AI Can Help Design Drugs to Treat Opioid Addiction
ROCKVILLE, MD – Approximately three million Americans suffer from opioid use disorder, and every year more than 80,000 Americans die from overdoses. Opioid drugs, such as heroin, fentanyl, oxycodone and morphine, activate opioid receptors. Activating mu-opioid receptors leads to pain relief and euphoria, but also physical dependence and decreased breathing, the latter leading to death in the case of drug overdose.
New Technique Maps Large-scale Impacts of Fire-induced Permafrost Thaw in Alaska
For the first time, researchers have developed a machine learning-based ensemble approach to quantify fire-induced thaw settlement across the entire Tanana Flats in Alaska, which encompasses more than 3 million acres. They linked airborne repeat lidar data to time-series Landsat products (satellite images) to delineate thaw settlement patterns across six large fires that have occurred since 2000. The six fires resulted in a loss of nearly 99,000 acres of evergreen forest from 2000 to 2014 among nearly 155,000 acres of fire-influenced forests with varying degrees of burn severity. This novel approach helped to explain about 65 percent of the variance in lidar-detected elevation change.
“Build Your Own Masters” at NYU Tandon
An innovative engineering master’s program unveiled today by Digital Learning at NYU Tandon gives students flexibility to tailor their degree to their unique professional interests and aspirations. Students will have the opportunity to enroll in one of nine interdisciplinary concentrations – including in-demand fields like robotics, cybersecurity, and data science – all offered fully online.
Addis Fuhr: Working to control impurities in materials
Oak Ridge National Laboratory Weinberg Fellow Addis Fuhr uses quantum chemistry and machine learning methods to advance new materials.
Argonne’s Sibendu Som named American Society of Mechanical Engineers Fellow
Sibendu Som, whose work focuses on high-fidelity simulations of power generation and propulsion systems, has been designated a fellow by the American Society of Mechanical Engineers.
Is brain learning weaker than artificial Intelligence?
Can the brain, with its limited realization of precise mathematical operations, compete with advanced artificial intelligence systems implemented on fast and parallel computers? From our daily experience we know that for many tasks the answer is yes! Why is this and, given this affirmative answer, can one build a new type of efficient artificial intelligence inspired by the brain? In an article published today in Scientific Reports, researchers from Bar-Ilan University in Israel solve this puzzle.
AI and health care: DePaul and Rosalind Franklin award interdisciplinary research grants
DePaul University and Rosalind Franklin University of Science and Medicine are funding three faculty research projects that bring together artificial intelligence, biomedical discovery and health care. The competitive grants kickstart research among interdisciplinary teams, which include biologists, computer scientists, a geographer and a physicist.