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.
Current AI models are restricted by a lack of experience in real-world environments, despite achieving significant advancements in virtual settings. Researchers are now exploring ways to bridge this gap with foundation models that can operate in physical spaces.
Physicists used machine learning to compress a complex quantum problem into four equations, capturing the physics of electrons on a lattice with high accuracy. The approach could revolutionize how scientists investigate systems containing many interacting electrons and potentially aid in designing materials with sought-after properties.
A public consultation is launched to develop best-practice standards for diverse and inclusive healthcare datasets used in Artificial Intelligence. The project aims to reduce biases that affect patients from minoritised racial/ethnic groups, ensuring they receive accurate predictions and treatments.
A new study by Eurac Research confirms negative global trends in mountain areas, with an average decline of 15 days of snow on the ground over 38 years. Snow cover has decreased by 4% globally, with peaks of 20 or more fewer days in Canada's western provinces.
Researchers developed an AI-based screening method that models drug and target protein interactions using natural language processing techniques. The technique achieved high accuracy in identifying promising drug candidates, which can accelerate the exploration of new medicines and repurpose existing ones.
A recent study found that individuals who distrust fellow humans tend to have more trust in artificial intelligence's ability to moderate content online. The researchers suggest personalizing interfaces based on individual differences can positively alter user experience.
Researchers developed an in-home wireless device that monitors a patient's movement and gait speed to track Parkinson's disease progression. The device uses machine-learning algorithms to analyze over 200,000 data points collected from 50 participants, showing that it can effectively track the severity of the disease.
Researchers at POSTECH have developed a method to engineer organs at scale using bioprinting, overcoming previous limitations of small tissue size and functional complexity. This innovation holds promise for personalized treatment of patients with the potential to create more realistic engineered organs.
A study from the University of Georgia shows people who rely on algorithms for creative tasks don't improve their performance and are more likely to trust low-quality advice. Participants preferred algorithm-derived advice over human-based advice, even when confident in their answers.
Sooby's research aims to develop an AI algorithm to rapidly provide high-quality data during alloy fabrication, reducing time and cost. Her lab collaborates with Computer Science professor Amanda Fernandez to leverage deep learning approaches for image labeling, increasing efficiency by 99%.
UC San Diego researchers created the first diagnostic tool to differentiate between Kawasaki Disease and Multisystem Inflammatory Syndrome in Children (MIS-C) using a novel artificial intelligence-guided algorithm. The algorithm achieved accuracy exceeding 90% with simple test results and physical exam features.
A University of Missouri researcher and his team are using artificial intelligence to study anatomical research, creating detailed 3D computer models of muscles. This technology is advancing the field by enabling researchers to analyze muscle fiber orientation and develop a better understanding of motor control in animals.
The MEMEX project promotes social cohesion by using AI and interactive tools to share community stories linked to cultural heritage. The exhibition features audio-visual stories from Lisbon, Barcelona, Paris, and Genoa participants who co-created their own digital content.
Researchers developed a mathematical model to analyze cognitive changes and impairment in the brain, applicable to multiple sclerosis and other neurodegenerative diseases. The model uses multilayer networks for comprehensive analysis of CT scans, X-rays, ultrasound, and magnetic resonance imaging data.
Researchers at Kyoto University designed a shared-laughter AI system to build empathy into dialogue between robots and humans. The system was tested on the Japanese android Erica, performing better than baseline models in evaluating empathy, naturalness, and human-likeness.
A team of researchers from Japan successfully reconstructed common brain input signals from the firing rates of neurons using a method called superposed recurrence plot. This breakthrough has significant implications for artificial intelligence, neuroscience, and potential treatments for mental health disorders.
A large-scale experimental study by Harvard, Stanford, and MIT researchers found that weaker social connections on LinkedIn have a greater beneficial effect on job mobility than stronger ties. Weaker ties increased the likelihood of job mobility the most, while strongest ties had the least impact.
Researchers designed an integrated system to support joint operations between UAVs and mobile robots for surveillance, epidemic prevention, and rescue operations. The system aims to improve public safety while ensuring privacy and security.
Researchers discovered varying attitudes towards AI ethics, legal issues, and social implications in Japan, the US, and Germany. The study found that older respondents were more concerned about AI and ELSI issues, while those familiar with AI prioritized legal concerns.
Using artificial intelligence, researchers from Tufts University have devised rules for faster and more effective identification of potential new drug cocktails against tuberculosis. The study developed a set of design principles to assemble drug combinations, reducing the amount of testing needed before moving to further study.
A study by Simon Dubé examines the personality traits of people willing to engage with sex robots, revealing that erotophilia, sexual sensation-seeking, and enthusiasm for new experiences are key drivers. The research highlights an opportunity for manufacturers to cater to a female customer base as technology improves and becomes more ...
The University of California, San Diego is part of the National Institutes of Health's Bridge to Artificial Intelligence program, aiming to create comprehensive AI-ready datasets. The program will support researchers in developing interpretable and trustworthy AI technologies to improve human health.
A new neural network model developed by Aalto University researchers can accurately predict the occurrence of fires in peatlands. The model identified a suite of interventions that would reduce fire incidence by 50-76%.
The NEUROCOV project seeks to understand the interplay between SARS-CoV-2 infection and the nervous system, with a focus on immune response and neuronal functions. The research aims to predict risk for neurological symptoms and develop effective treatments.
Researchers find XAI methods improve AI performance and explain bias in data, enabling accurate applications like insurance decision-making. Implementing XAI helps manage power consumption and optimize AI systems for efficient Industry 4.0 growth.
A new study from MIT reveals that computer models predicting molecular interactions, like AlphaFold, need improvement to help identify drug mechanisms of action. Researchers improved the performance of these models using machine-learning techniques, but more work is needed.
A study by NTU Singapore found that people have lower trust in health interventions suggested by AI alone, compared to those they perceive as based on human expert opinion. Emphasizing the involvement of a human health expert can improve acceptance and effectiveness of AI-suggested preventive care measures.
Researchers created IGLUE to score ML efficiency in 20 languages, addressing cultural bias and practical implications. The tool aims to improve solutions for visually impaired and reduce performance dropouts outside English-speaking contexts.
Machine learning helps researchers discover how bacterial populations adapt to environmental diversity by analyzing growth curves. The analysis reveals distinct decision-making components for lag, growth, and saturation phases, protecting the population from extinction.
A team from Ruhr-Universität Bochum developed a novel neural network that can classify tissue samples as containing tumors or not. The AI also generates an activation map showing where the tumor is detected, based on falsifiable hypotheses.
Researchers analyzed 170,000 vegetation plots from all climate zones to find that small areas can have high biodiversity, like Eastern European steppes and Siberia. This challenges the idea of large-scale conservation, as smaller protected zones may be more effective in preserving ecosystems.
A machine-learning model developed at Mass Eye and Ear accurately diagnosed pediatric ear infections at a rate 30 percent higher than doctors surveyed. The model achieved 95% accuracy in diagnosing an ear infection from test images, surpassing the average clinical accuracy of 65%.
Researchers used data from over 66,000 deliveries to create a prediction model that analyzes patterns of changes in women in labor. The algorithm aims to reduce cesarean delivery rates and maternal/neonatal complications by providing real-time risk predictions.
A new method for generating realistic images in driving simulations uses machine learning to improve visual fidelity. This enables better testing of driverless cars and study of driver distraction, ultimately enhancing safety and interaction between humans and AI on the road.
Rice University's ROBE Array algorithm slashes the size of DLRM memory structures, allowing training on 100 megabytes of memory and a single GPU. The method matches state-of-the-art DLRM training methods with improved inference efficiency.
Researchers at the University of Oldenburg and Fraunhofer IWES collaborate on a new project to develop more accurate wind flow simulations using artificial intelligence. The goal is to reduce computing times and enhance precision, ultimately accelerating innovation in wind turbine design.
ORNL researchers have won seven 2022 R&D 100 Awards for their advancements in materials science, machine learning, and energy storage. DuAlumin-3D, a high-strength aluminum alloy, and Gremlin, an AI system to identify weaknesses in machine learning models, are among the winning technologies.
Researchers developed an algorithm to identify different regions within tumors using nearly 6,500 digital slide images. The algorithm can predict recurrence-free survival and help guide therapy for patients with colon cancer.
Researchers at MIT developed an AI model that can detect Parkinson's disease from breathing patterns, using a neural network to assess the presence and severity of the condition. The device is non-invasive and can be used in patients' homes without any bodily contact.
Researchers developed an AI algorithm that can learn independently from multiple medical institutions without compromising data privacy. The algorithm outperformed traditional methods and has the potential to revolutionize digital medicine by reducing radiologists' workloads and making AI-based solutions more affordable.
A new study by the University of Central Florida reveals that workers in countries with greater income inequality are more likely to perceive robots and artificial intelligence as job threats. This association was found despite the potential benefits of these technologies to improve work and increase flexibility.
Researchers at NC State University have developed a cooperative distributed algorithm that allows autonomous vehicle software to make calculations more quickly, enabling real-time navigation of complex merging scenarios. The approach improves both traffic flow and safety, with zero incidents in simulations.
A new study found that over 50% of Gen Z respondents were concerned about the use of non-conscious data collection (NCDC), with attitudes varying by gender, income, education level, and religion. The study proposed a "mind-sponge" model-based approach to account for socio-cultural factors in assessing AI technology acceptance.
Researchers developed a machine learning algorithm that can predict how different driving patterns affect battery performance, improving safety and reliability. The algorithm uses non-invasive probing to provide a holistic view of battery health, suggesting routes and driving patterns that minimize degradation and charging times.
Researchers at Stanford University have created a new chip architecture called NeuRRAM that performs AI computing directly within memory, reducing energy consumption and increasing efficiency. The chip has been tested on various AI tasks and shown high accuracy rates.
A team of researchers from Osaka University developed an AI algorithm to predict the risk of mortality for trauma patients. They analyzed a large dataset of patient information and blood markers to identify critical factors that guide treatment strategies more precisely.
A new evaluation method at Osaka University accurately compares android and human facial expressions. The study found that androids have significantly less expressiveness than humans, but the new index may aid in developing more lifelike robots.
Researchers identified robust metabolic markers of Covid, leading to better understanding and treatments for post-diagnosis symptoms. The study found that effects of Covid changed over time, persisting in some patients months after recovery.
A new method, XTEC, uses machine learning to analyze large volumes of X-ray data, revealing previously hidden structural changes in materials. This accelerates materials discoveries and unlocks new properties of temperature-sensitive devices.
A new University of Illinois project aims to improve undergraduate students' ability to estimate their knowledge using artificial intelligence methods. The researchers will utilize machine learning to anticipate student performance and provide personalized feedback to enhance studying strategies.
A new AI algorithm has been developed to detect subtle brain abnormalities causing epileptic seizures. The Multicentre Epilepsy Lesion Detection project used over 1,000 patient MRI scans to train the algorithm, which was able to detect focal cortical dysplasia (FCD) in 67% of cases. This could lead to more patients being considered for...
A team of researchers at USC has developed a system to quantify and fix anti-queer bias in AI-powered text prediction. By training the popular language model BERT on queer-inclusive data from Twitter and news articles, they significantly reduced biases in predictions, with QueerTwitter showing the most effective results.
MIT researchers developed a method to create 3D-printed materials with tunable mechanical properties and embedded sensors, enabling real-time feedback on movement and interaction. The sensing structures use air-filled channels that deform when moved or squeezed, providing accurate feedback for robotics and wearable devices.
Researchers developed a Flashover Prediction Neural Network (FlashNet) model to forecast deadly fire events, beating other AI-based tools with up to 92.1% accuracy across various building floorplans. The model's performance improved when given real-world data, highlighting its potential for saving firefighter lives.
A new study by Petra Nieken found that charismatic leadership tactics and consistent video communication lead to better performance in remote work. In contrast, traditional charisma questionnaires did not predict staff performance. The study suggests that managers should convey a consistent impression when using the video channel.
Researchers at UNH will develop and test social assistive robots to aid in the care of individuals with Alzheimer’s disease and related dementia in their own homes. The robots will be equipped with smart home devices, artificial intelligence, and wearables to track patients' activity levels and health management.
Researchers at Carnegie Mellon University have developed an AI pilot that can safely navigate crowded airspace by predicting the intent of other aircraft and avoiding collisions. The AI uses vision and natural language processing to communicate with other aircraft, enabling safe and socially compliant navigation.
Researchers have developed a proof-of-concept model that uses artificial intelligence to combine multiple types of data from different sources to predict patient outcomes. The models demonstrate the ability to make prognostic determinations while uncovering the predictive bases of features used to predict patient risk.
The University of Illinois School is awarding a grant to explore the use of conversational AI in libraries, aiming to strengthen engagement between libraries and diverse audiences. The project will investigate ways to democratize conversational AI for librarians, enhancing workforce development and community service.
Researchers developed a flexible, stretchable computing chip that processes information like a human brain to analyze health data. The device aims to change the way health data is processed, enabling continuous tracking of health without sending data wirelessly.