Articles tagged with Artificial Intelligence
Comprehensive exploration of living organisms, biological systems, and life processes across all scales from molecules to ecosystems. Encompasses cutting-edge research in biology, genetics, molecular biology, ecology, biochemistry, microbiology, botany, zoology, evolutionary biology, genomics, and biotechnology. Investigates cellular mechanisms, organism development, genetic inheritance, biodiversity conservation, metabolic processes, protein synthesis, DNA sequencing, CRISPR gene editing, stem cell research, and the fundamental principles governing all forms of life on Earth.
Comprehensive medical research, clinical studies, and healthcare sciences focused on disease prevention, diagnosis, and treatment. Encompasses clinical medicine, public health, pharmacology, epidemiology, medical specialties, disease mechanisms, therapeutic interventions, healthcare innovation, precision medicine, telemedicine, medical devices, drug development, clinical trials, patient care, mental health, nutrition science, health policy, and the application of medical science to improve human health, wellbeing, and quality of life across diverse populations.
Comprehensive investigation of human society, behavior, relationships, and social structures through systematic research and analysis. Encompasses psychology, sociology, anthropology, economics, political science, linguistics, education, demography, communications, and social research methodologies. Examines human cognition, social interactions, cultural phenomena, economic systems, political institutions, language and communication, educational processes, population dynamics, and the complex social, cultural, economic, and political forces shaping human societies, communities, and civilizations throughout history and across the contemporary world.
Fundamental study of the non-living natural world, matter, energy, and physical phenomena governing the universe. Encompasses physics, chemistry, earth sciences, atmospheric sciences, oceanography, materials science, and the investigation of physical laws, chemical reactions, geological processes, climate systems, and planetary dynamics. Explores everything from subatomic particles and quantum mechanics to planetary systems and cosmic phenomena, including energy transformations, molecular interactions, elemental properties, weather patterns, tectonic activity, and the fundamental forces and principles underlying the physical nature of reality.
Practical application of scientific knowledge and engineering principles to solve real-world problems and develop innovative technologies. Encompasses all engineering disciplines, technology development, computer science, artificial intelligence, environmental sciences, agriculture, materials applications, energy systems, and industrial innovation. Bridges theoretical research with tangible solutions for infrastructure, manufacturing, computing, communications, transportation, construction, sustainable development, and emerging technologies that advance human capabilities, improve quality of life, and address societal challenges through scientific innovation and technological progress.
Study of the practice, culture, infrastructure, and social dimensions of science itself. Addresses how science is conducted, organized, communicated, and integrated into society. Encompasses research funding mechanisms, scientific publishing systems, peer review processes, academic ethics, science policy, research institutions, scientific collaboration networks, science education, career development, research programs, scientific methods, science communication, and the sociology of scientific discovery. Examines the human, institutional, and cultural aspects of scientific enterprise, knowledge production, and the translation of research into societal benefit.
Comprehensive study of the universe beyond Earth, encompassing celestial objects, cosmic phenomena, and space exploration. Includes astronomy, astrophysics, planetary science, cosmology, space physics, astrobiology, and space technology. Investigates stars, galaxies, planets, moons, asteroids, comets, black holes, nebulae, exoplanets, dark matter, dark energy, cosmic microwave background, stellar evolution, planetary formation, space weather, solar system dynamics, the search for extraterrestrial life, and humanity's efforts to explore, understand, and unlock the mysteries of the cosmos through observation, theory, and space missions.
Comprehensive examination of tools, techniques, methodologies, and approaches used across scientific disciplines to conduct research, collect data, and analyze results. Encompasses experimental procedures, analytical methods, measurement techniques, instrumentation, imaging technologies, spectroscopic methods, laboratory protocols, observational studies, statistical analysis, computational methods, data visualization, quality control, and methodological innovations. Addresses the practical techniques and theoretical frameworks enabling scientists to investigate phenomena, test hypotheses, gather evidence, ensure reproducibility, and generate reliable knowledge through systematic, rigorous investigation across all areas of scientific inquiry.
Study of abstract structures, patterns, quantities, relationships, and logical reasoning through pure and applied mathematical disciplines. Encompasses algebra, calculus, geometry, topology, number theory, analysis, discrete mathematics, mathematical logic, set theory, probability, statistics, and computational mathematics. Investigates mathematical structures, theorems, proofs, algorithms, functions, equations, and the rigorous logical frameworks underlying quantitative reasoning. Provides the foundational language and tools for all scientific fields, enabling precise description of natural phenomena, modeling of complex systems, and the development of technologies across physics, engineering, computer science, economics, and all quantitative sciences.
PaSh parallelizes Unix shell scripts automatically and accurately, boosting execution speeds by hundreds of times. Researchers tested the system on hundreds of scripts and found no errors, making it accessible to data scientists, biologists, engineers, and economists.
A study found that the brain uses data compression to eliminate irrelevant information and adopt temporary 'tunnel vision' for optimal performance. This principle extends beyond sensory processing to cognitive functions.
The study explored how humans react to AI decision making by studying human interaction with autonomous cars. Researchers found that people show an aversion to AI when asked explicitly, but not when not being asked, and that this rejection is mostly due to incorporating individuals' beliefs about society's opinion.
Researchers used AI to compare brain images of individuals with Autism Spectrum Disorder to computer-generated simulations, revealing links between brain anatomy and symptoms. The discovery could help understand ASD causes and develop targeted interventions.
Researchers at Oak Ridge National Laboratory have made significant advancements in recovering rare earth metals, developing safer batteries, and enhancing material properties through tailored molecules and advanced microscopy. These discoveries could lead to more efficient clean energy technologies and reduced carbon impacts.
Researchers have created prototypes that provide text descriptions at varying levels of detail, enabling blind and low-vision individuals to drill down from high-level data to more detailed information using just a few keystrokes. The prototypes improved users' ability to identify patterns in the data and navigate through visualization...
Ingmar Weber's research focuses on societal computing, using computer science methods to understand and improve society. He collaborates with various stakeholders, including the UN, to develop solutions for humanitarian crises.
Researchers at MIT found that explanation methods used to aid human decision-makers in high-stakes situations often have lower accuracy for minoritized subgroups. The fidelity of these explanations varies dramatically between subgroups, with the quality often significantly lower for women and Black people.
A study conducted by Kaunas University of Technology researchers analyzed how people with Alzheimer's disease process visual information from faces. The study found that brain signals in patients are significantly noisier, making it harder for them to focus and be attentive.
Academics argue AI systems like DABUS need new IP laws as existing ones are inadequate to deal with cases where machines are named sole inventors. The authors recommend introducing a new 'AI-IP' form of law that would be specifically tailored to AI-generated inventiveness, addressing ownership and novelty issues.
The Frontier supercomputer has achieved an unprecedented level of computing performance, breaking the exascale barrier with 1.1 exaflops of performance. This milestone enables scientists to tackle previously unsolvable problems in fields like energy and national security.
The Collaborative Research Centre Hearing Acoustics is developing smart hearing aids that use artificial intelligence to adjust to different environments. The project, which aims to create more adaptable hearing devices, has received $8.1 million in funding for another four years.
Researchers use AI software to identify invasive species and native trees threatened by disease from photos taken by on-train cameras. This technology enables railway workers to take action to better manage lineside vegetation and achieve biodiversity net gain by 2035.
The CONCERN initiative uses AI to analyze nursing documentation and predict patient outcomes, such as organ failure or cardiac arrest. By leveraging nurse expertise, the tool aims to improve patient care and reduce preventable deaths.
A new training program at MUSC and Clemson University aims to make future data scientists aware of health inequities, particularly in rural communities. The SC BIDS4HEALTH program will build on existing relationships with HBCUs and community groups across the state.
MIT researchers develop an interactive design pipeline enabling users to create customized robotic hands with tactile sensors. The platform streamlines the process, allowing users to adjust palm and fingers and integrate tactile sensors, resulting in complex tasks like picking delicate items or using tools being performed flawlessly.
A machine learning algorithm has outperformed astronomers in analyzing microlensing data to find new exoplanets, revealing connections hidden in complex mathematics from general relativity. The AI algorithm uncovered a degeneracy that had been missed by experts, suggesting a broader theory is likely incomplete.
Researchers have successfully processed sequences with a large neural network while consuming significantly less energy on neuromorphic hardware. This breakthrough showcases the potential of neuromorphic technology to improve the energy efficiency of AI workloads.
A new computer-aided diagnostic tool, Deep-Lung Parenchyma-Enhancing (DLPE), uses artificial intelligence to reveal signs of pulmonary fibrosis in COVID long-haulers, helping to explain respiratory symptoms and improve disease management.
Veterinarians at UC Davis have developed an AI model that can predict Leptospirosis in dogs with high accuracy, outperforming traditional testing methods. The model uses machine-learning algorithms to analyze historical data and provide timely predictions, which can be an online resource for veterinarians.
A new smartphone app using AI technology has been found to be as accurate as expert gastroenterologists in characterizing stool specimens. The app's ability to provide detailed descriptions of constipation, diarrhea, and normal stools surpasses that of patient reports.
Researchers at MIT developed a technique that enables an autonomous vehicle to plot a provably safe trajectory in highly uncertain situations. The algorithm considers probability of observing different environmental conditions and obstacles, and formulates trajectory planning as a probabilistic optimization problem.
Researchers found that computer assistance in design leads to better solutions but compromises creativity and user agency. In a virtual reality experiment, novice designers outperformed their human-led counterparts when using an optimized approach.
A new method for 3D mapping uses artificial intelligence to detect correspondences and correct gaps in laser-point clouds, eliminating the need for manual data corrections. This approach enables faster, cheaper, and more accurate maps, with potential applications in construction, climate change monitoring, and road safety.
Researchers at ETH Zurich have developed a novel memristor design that can switch between two operation modes, enabling greater efficiency in machine learning applications. This breakthrough component is made of halide perovskite nanocrystals and simulates complex neural networks with high accuracy.
A new distributed learning technique, GD-SEC, reduces communication requirements in wireless architecture, improving efficiency and reducing computational cost. The method employs data compression to transmit only meaningful, usable data, enhancing the impact of machine learning while minimizing its limitations.
A new study demonstrates a machine-learning approach that can learn to control a fleet of autonomous vehicles as they approach and travel through a signalized intersection. The technique reduces fuel consumption and emissions while improving average vehicle speed, with benefits seen even when only 25% of cars use the control algorithm.
A team from the University of Missouri is using artificial intelligence to accelerate the discovery process in materials science. By integrating machine learning algorithms and AI into traditional laboratory processes, they aim to reduce time and cost while increasing the rate of material development. Associate Professor Derek T. Ander...
A new software uses natural language processing to predict vaccine hesitancy on a community level, providing an early warning system for policymakers. The study shows that publicly available Twitter data can be sufficient to detect zip code-level vaccine hesitancy with reasonable accuracy.
A new approach using artificial intelligence generates designs automatically, allowing researchers to create complex metasurfaces with billions of nanopillars. This enables the development of larger, more complex metalenses for virtual reality and augmented reality systems.
A new algorithm forecasts which hospitalized patients are at the highest risk of death from COVID-19, regardless of immune protection status or virus variant. The tool, called COVID-19 Disease Outcome Predictor (CODOP), uses blood measurements to predict prognosis and can help direct critical care resources.
Researchers have developed CAS(ME)3, a large-scale micro-expression database with depth information and high ecological validity. The database contains 1,109 manually labeled micro-expressions and 3,490 macro-expressions, allowing for more accurate emotional analysis and recognition.
Researchers at UC San Diego School of Medicine found that COVID-19, MIS-C and Kawasaki disease share similar underlying molecular patterns. The study reveals that MIS-C is a more severe version of the immune response than KD, with potential implications for improved disease diagnosis and treatment.
Xie aims to develop algorithms that reflect human domain knowledge and reasoning patterns, increasing trust in machine learning models. He also explores algorithmic fairness, considering multiple perspectives on what's considered fair, to address concerns about biased decision-making.
Researchers at Stevens Institute of Technology developed an underwater robot capable of mapping its environment, tracking its location, and planning safe routes in complex marine environments. The breakthrough enabled the robot to accurately map a busy harbor in real-time using active SLAM algorithms.
Researchers used game theory to create models of cooperative and competitive behaviors in multi-agent systems, focusing on distributed online optimization, federated optimization, and static/dynamic games. The findings have potential applications in smart cities, market competition, information security, and drug development.
An artificial intelligence model trained on histological images of surgical specimens accurately classified patients with and without Crohn disease recurrence. The model revealed previously unrecognized differences in adipose cells and mast cell infiltration, enabling stratification by prognosis for postoperative Crohn disease patients.
The university's new Robotics and Autonomous Systems Teaching and Innovation Center (RASTIC) will provide students with hands-on experience in robotics, autonomous systems, and self-driving technology. The lab aims to boost Massachusetts' competitiveness in the tech sector by supporting innovative projects and startups.
MIT researchers develop ExSum, a framework to formalize explanations of machine-learning models into quantifiable rules. This allows for testing assumptions about model behavior and reveals unexpected insights, such as negative words having sharper contributions to model decisions.
A new study uses artificial intelligence to predict bone fractures in cancer patients by creating a digital twin of the vertebra. The AI-assisted framework, ReconGAN, simulates how tumors affect the spine and predicts fracture risks, offering medical experts better treatment strategies and patient decisions.
A new $5 million center, MIXR, aims to develop, test and certify XR technologies in medicine and healthcare. The collaboration between academia, industry and government will improve medical training, patient management and health outcomes.
Artificial Intelligence can now identify legendary batting techniques used by Sir Donald Bradman and modern players. Researchers developed a deep learning computer vision AI model to detect lateral backlift batters from straight ones.
Researchers at Texas A&M University used an Artificial Intelligence Materials Selection framework to discover a new shape memory alloy with the highest efficiency ever recorded. The alloy's narrow transformation temperature window and high cyclic stability make it ideal for thermal energy harvesting and storage.
Researchers at the University of Missouri are applying AI to analyze protein dynamics, identifying potential target sites for new drug therapies. The approach can simulate protein changes related to conditions like cancer, enhancing the chances of successful therapies.
Researchers developed an AI algorithm that can detect weak heart pumps in patients using single-lead Apple Watch ECGs. The study found high participation rates and high-quality data from over 46 states and 11 countries, demonstrating the potential for this tool to be widely used.
A new study from Mayo Clinic suggests that AI-enabled electrocardiograms (ECGs) can predict atrial fibrillation, a cardiac rhythm abnormality linked to one-third of ischemic strokes. The algorithm also detects other cardiac disease markers and correlates with small vessel cerebrovascular disease and cognitive decline.
Researchers at Cedars-Sinai have developed an AI tool that accurately predicts pancreatic cancer patients based on CT scan images. Lowering blood cholesterol has also been shown to slow the growth of prostate cancer by enhancing immune cell action. Additionally, a new study found that an ultrasound probe plugged into a smartphone can b...
Researchers from Dartmouth College used artificial intelligence to draft wine and beer reviews, finding agreement between human and machine-generated reviews. The team also developed a system to write review syntheses, aggregating elements from existing reviews to provide limited but relevant information about products.
A new case study reveals significant differences between human and AI perception in breast-cancer screenings. Researchers found that AI systems consider tiny details in mammograms that are irrelevant to radiologists, highlighting the need for understanding and correcting AI decision-making before trusting it for life-critical medical d...
Researchers from Tokyo University of Science have designed a tunable physical reservoir device based on dielectric relaxation at an electrode-ionic liquid interface. The system can store and process analog signals, enabling real-time processing of signals in living environments.
Researchers at Johns Hopkins Medicine developed an AI training strategy to capture images of mouse brain cells in action, allowing scientists to understand how the brain functions and is affected by disease. The technology combines ultra-small microscopes with AI to enhance image resolution up to 52 frames per second.
A new AI-based method distinguishes between stable and progressive cognitive impairment, enabling accurate diagnosis with an accuracy rate of 85%. This technique overcomes the complexity of subtle structural changes in mild cognitive impairment, contributing to achieving Sustainable Development Goal 3.
Researchers used AI technologies to conclude that male characters are four times more prevalent in literature than female characters. The study's findings also showed that the discrepancy between male and female characters decreases under female authorship.
Researchers from the University of Cambridge have developed a hybrid, data-driven approach to the Travelling Salesperson Problem that significantly outperforms current methods. The new approach converges to optimal solutions at a faster rate and produces high-quality solutions under restricted computation time.
Researchers at MIT developed an AI method that constrains machine-learning models to suggest molecules with producible chemical structures. The approach guarantees quality and speed, outperforming existing methods in proposing high-quality molecular structures.
A new study indicates that artificial intelligence can accurately predict who will develop pancreatic cancer based on pre-diagnostic CT scan images. The AI tool was trained to analyze textural differences in the pancreas and achieved an accuracy rate of 86% in identifying those who would eventually develop the disease.
Researchers developed a machine-learning method that allows robots to pick up and place never-before-seen objects in random poses, requiring only 10 human demonstrations. The system uses a neural network specifically designed to reconstruct 3D shapes, enabling the robot to generalize to new object orientations.
Researchers developed an AI system using swarm learning to predict cancer from medical images of tissue samples without accessing patient data. The technique improved the detection of genetic changes in colon tumors with high accuracy.
Researchers at Michigan State University have designed a learning-enabled safe controller for systems operating in uncertain environments. The new method, which combines control barrier functions and Lyapunov functions, allows the system to quickly learn uncertainties while achieving maximum safe performance.
A recent study found that an artificial intelligence-based system improved providers' assessments of bladder cancer patients' response to chemotherapy. The AI tool helped doctors from different specialties and experience levels make more accurate diagnoses, with those in academia showing the greatest gains.