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Continuous, unobtrusive sensors and related monitoring devices are installed in older drivers’ vehicles to detect changes in highly complex activities over time. A driver facing camera, forward facing camera, and telematics unit provide video in real-time to enable researchers to analyze abnormal driving such as getting lost, reaction time and braking patterns as well as travel patterns such as miles driven, miles during the night and daytime, and driving in severe weather. Detecting changes in behavior could generate early warning signs of possible changes in cognition.

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A recent study introduce a novel paradigm combining ChatGPT with machine learning (ML) to significantly ease the application of ML in environmental science. This approach promises to bridge knowledge gaps and democratize the use of complex ML models for environmental sustainability.

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Digital Science announces two new products – Dimensions Research GPT and Dimensions Research GPT Enterprise – bringing the unmatched, trusted research coverage of Dimensions to the ChatGPT platform.

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Researchers at the Icahn School of Medicine at Mount Sinai and others have harnessed the power of machine learning to identify key predictors of mortality in dementia patients. The study, published in the February 28 online issue of Communications Medicine, addresses critical challenges in dementia care by pinpointing patients at high risk of near-term death and uncovers the factors that drive this risk. Unlike previous studies that focused on diagnosing dementia, this research delves into predicting patient prognosis, shedding light on mortality risks and contributing factors in various kinds of dementia.

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Bridging precision engineering and precision medicine to create personalized physiology avatars. Pursuing on-demand tissue and organ engineering for human health. Revolutionizing neuroscience by using AI to engineer advanced brain interface systems. Engineering the immune system for health and wellness. Designing and engineering genomes for organism repurposing and genomic perturbations.

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Two leading multiple sclerosis (MS) experts—Nancy Sicotte, MD, director of Multiple Sclerosis and Neuroimmunology at Cedars-Sinai, and Pascal Sati, PhD, director of the Neuro Imaging Program in the Department of Neurology—are attending the Americas Committee for Treatment and Research in Multiple Sclerosis Forum 2024 Feb. 29-March 2 in West Palm Beach, Florida.

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The Technology Infrastructure for Data Exploration (TIDE) project at SDSU will give CSU researchers access to new high-performance data processing capabilities.

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Researchers at the University of Notre Dame conducted a study using AI bots based on large language models and asked human and AI bot participants to engage in political discourse. Fifty-eight percent of the time, the participants could not identify who the AI bots were.

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Too often, the first sign of cardiovascular disease may be a major event like a heart attack, stroke or cardiac arrest. Now, researchers and clinicians at Mayo Clinic are using artificial intelligence (AI) technology to flag heart problems earlier, boosting the abilities of a diagnostic test that has been around for over a century — the electrocardiogram (ECG).

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Liberating Greatness in Every Neurosurgeon, AtlasGPT Delivers the Most Trusted Decision Support for Brain and Spine Care

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Practice makes perfect, and a new system being tested and perfected that enables surgical trainees to obtain cutting-edge instruction in real-time, all through a new artificial intelligence program. As medical students conduct surgical exercises, the AI software scans a live video feed and provides immediate, personalized feedback.The solution is among the first generation of AI teachers giving real-time feedback and may pioneer the use of similar instructional technology in other industries, including additional areas of healthcare and medicine.

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With time scheduled to use a certain beamline at the National Synchrotron Light Source-II (NSLS-II), scientists from NSLS-II and their partner institutions faced a challenge. They planned on researching a special type of region in magnetic materials that could be useful for next-generation computers. Regions in magnetic materials - called magnetic domains - determine a material's magnetic properties. The scientists wanted to study how these magnetic domains changed over time under the influence of an outside magnetic field.

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An interdisciplinary team of experts from the University of Notre Dame, in collaboration with the University of Maryland and University of Utah, have found a way to use artificial intelligence to analyze a household’s passive design characteristics and predict its energy expenses with more than 74 percent accuracy. By combining their findings with demographic data including poverty levels, the researchers have created a comprehensive model for predicting energy burden across 1,402 census tracts and nearly 300,000 households in Chicago.

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From the invention of the wheel to the advent of the printing press to the splitting of the atom, history is replete with cautionary tales of new technologies emerging before humanity was ready to cope with them.

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With national elections looming in the United States, concerns about misinformation are sharper than ever, and advances in artificial intelligence have made distinguishing genuine news sites from fake ones even more challenging. Virginia Tech experts explore three different facets of the AI-fueled spread of fake news sites and the efforts to combat them.

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Researchers have paired a deep learning model with experimental data to “decode” mouse neural activity.

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ETRI’s researchers have unveiled a technology that combines generative AI and visual intelligence to create images from text inputs in just 2 seconds, propelling the field of ultra-fast generative visual intelligence.

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A Princeton-led team composed of engineers, physicists, and data scientists from the University and the Princeton Plasma Physics Laboratory (PPPL) have harnessed the power of artificial intelligence to predict — and then avoid — the formation of a specific plasma problem in real time.

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Two teams of engineers led by faculty in the McKelvey School of Engineering at Washington University in St. Louis will work toward developing products to monitor drinking water quality and to detect explosives with an electronic nose with one-year, $650,000 Convergence Accelerator Phase 1 grants from the National Science Foundation (NSF).

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Researchers at West Virginia University have identified a set of diagnostic metabolic biomarkers that can help them develop artificial intelligence tools to detect Alzheimer’s disease in its early stages, as well as determine risk factors and treatment interventions.

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Dustin Tyler, the Kent H. Smith II Professor of Biomedical Engineering at CWRU’s Case School of Engineering, co-founded a company that restores for people the sensation of touch—with help from a set of electrical rings that fit snugly on users’ fingers—from a distance.

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ETRI’s researchers have pioneered the development of light source devices that can be utilized in mega/hyper datacenters and 5G/6G mobile communication base stations. The technology innovated by the research team can transmit full HD movies of 5 GB size at a rate of 5.6 per second.

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Imageomics, a new field of science, has made stunning progress in the past year and is on the verge of major discoveries about life on Earth, according to one of the founders of the discipline. Tanya Berger-Wolf, faculty director of the Translational Data Analytics Institute at The Ohio State University, outlined the state of imageomics in a presentation at the annual meeting of the American Association for the Advancement of Science.

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The random information posted online could be used to generate information about biodiversity and its conservation.

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Researchers studying complex phenomena such as the Higgs boson must work with massive experimental data sets. To help, researchers have defined practical FAIR (findable, accessible, interoperable, reusable) principles for data and applied the principles to an open simulated tktk from CERN. FAIR will help humans and computers use large data sets, enable modern computers to process these data sets, and aid the development of artificial intelligence tools.

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A research team at Los Alamos National Laboratory is using artificial intelligence to address several critical shortcomings in large-scale malware analysis, making significant advancements in the classification of Microsoft Windows malware and paving the way for enhanced cybersecurity measures. Using their approach, the team set a new world record in classifying malware families.

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By integrating an ensemble of privacy-preserving algorithms, a KAUST research team has developed a machine-learning approach that addresses a significant challenge in medical research: How to use the power of artificial intelligence (AI) to accelerate discovery from genomic data while protecting the privacy of individuals

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Mike Teodorescu, a University of Washington assistant professor in the Information School, proposes that private enterprise standards for fairer machine learning systems would inform governmental regulation.

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Irvine, Calif., Feb. 15, 2024 – Throughout human history, technologies have been used to make peoples’ lives richer and more comfortable, but they have also contributed to a global crisis threatening Earth’s climate, ecosystems and even our own survival.

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The in silico trial demonstrated 2X the efficacy of the current treatment (>80% vs 39%); 3X shorter treatment time to cure (6 vs 18 months); 1 drug compared to a 3-drug combo for the standard of care; and preclinical results in shorter time than animal models.

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Researchers at the U.S. Department of Energy’s Argonne National Laboratory have used new generative AI techniques to propose new metal-organic framework materials that could offer enhanced abilities to capture carbon

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A collaborative group of investigators used artificial intelligence (AI) to quickly and accurately measure fat around the heart using a low-dose computed tomography (CT) scan during a routine test.

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Electronics and Telecommunications Research Institute (ETRI) has developed a technology that recognizes real-time game situations by analyzing play elements extracted from game videos and automatically generates highlights by identifying key play events in the game.

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Issues such as abrupt changes in speed limits and incomplete lane markings are among the most influential factors that can predict road crashes, finds new research by University of Massachusetts Amherst engineers.

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Researchers have developed the largest-ever dataset of biological images suitable for use by machine learning – and a new vision-based artificial intelligence tool to learn from it.

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A West Virginia University urban forester is developing a method — with the help of artificial intelligence — to identify trees at risk of falling on power lines and causing blackouts.

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UMD Smith expert explains the wave of tech job layoffs as a sign of a broader, labor market shift to where “humans need to recalibrate and capitalize on strengths beyond pure intelligence—like intuition, empathy, creativity, emotion and people skills.”

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Surgeons and investigators from Cedars-Sinai Orthopaedics bring their leading-edge expertise in treatment and the latest clinical research to the annual meeting of the American Academy of Orthopaedic Surgeons (AAOS) in San Francisco February 12-16.

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With the growing popularity of large language model (LLM) chatbots, a type of artificial intelligence (AI) used by ChatGPT, Google Bard and BingAI, it is important to outline the accuracy of musculoskeletal health information they provide.

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Imagine a world in which the digital watch on your wrist tracks not only your step count, but also your blood sugar, heart rate, blood pressure and respiration.

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Past attendees of the annual Argonne Training Program on Extreme-Scale Computing are thriving in careers across the field of high performance computing.

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Artificial intelligence (AI) chatbots are more accurate than expected when asked to answer medical questions about spine surgery, but patients still need to use extreme caution when turning to these tools for help with medical decision-making.