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.
Researchers created a new set of standards, called FAIR, to manage AI models, making them findable, accessible, interoperable and reusable. This standardization enables cross-pollination across teams and reduces duplication of effort, ultimately facilitating scientific discovery.
Experts warn that poorly functioning IT systems are a clear and present threat to patient safety, resulting from inadequate investment and lack of prioritization. The British Medical Association estimates that 27% of clinicians lose over four hours a week due to inefficient IT systems, highlighting the need for urgent improvement.
The DUNE project uses deep learning techniques and distributed computing to improve indoor positioning accuracy. The system combines various sensor technologies and adapts to different industrial needs, providing real-time updates and reducing margins of error.
Researchers have demonstrated a power-efficient component for demultiplexing operation using silicon photonic MEMS, enabling efficient wavelength demultiplexing for fiber-optic communications. The compact footprint of the add-drop filter allows fast operation compared to established MEMS products.
The University of Tsukuba researchers developed a machine-learning model to predict undertriage in phone-based triage systems. The model identified risk factors such as age, sex, and comorbid conditions, which can be used to update protocols and improve patient outcomes.
A new AI technology has been developed to automatically diagnose lung diseases such as tuberculosis and pneumonia, freeing up radiographers and reducing waiting times for test results. The system, which uses X-ray imaging and deep learning algorithms, achieved a 98% accuracy rate during extensive testing.
Researchers developed an intelligent compaction technology that integrates into a road roller, assessing real-time the quality of road base compaction. This improves road construction, reducing potholes and maintenance costs, leading to safer and more resilient roads.
NJIT Assistant Professor Salam Daher is using augmented reality technology to train caretakers for the elderly. The project aims to improve communication and empathy skills through a digital model of an older person that responds to emotions and environment. The system will be tested to investigate its impact on patient outcomes.
A new research group aims to develop an interdisciplinary approach for secure operation of critical infrastructure systems using artificial intelligence. The goal is to create a 'hybrid architecture' that combines AI-based strategic development with rule-based systems, ensuring safe and reliable behavior.
The National Science Foundation has awarded $800,000 to support the development of Edge AI applications in a proposed wearable diabetes management device. The project aims to create a smart, wearable device that monitors blood sugar levels without the need for frequent blood draws, reducing delays and increasing privacy and security.
Researchers from Osaka University have developed an AI-powered method to identify optimal amino acid mutations in enzymes. This approach accelerates the enzyme engineering process, allowing for tailored enzyme designs suitable for various biochemical environments.
Researchers at the University of Houston are developing a clinical decision support system to predict which patients with diabetes are most likely to experience complications. The tool, called Primary Care Forecast, uses deep learning to consider patient health history and social factors such as employment status and education level.
Deep learning models can become less accurate in recognizing specific categories of images, sounds, or text after network pruning. Researchers demonstrate a technique to address this challenge, improving the fairness of deep learning models.
The US Department of Energy's Oak Ridge National Laboratory has developed a massive geographic dataset, USA Structures, using deep learning to forecast potential damage and accelerate emergency response. The dataset provides critical information on building outlines and attributes, enabling FEMA to prioritize response efforts.
A new AI framework, M2YOLOF, has been proposed for fast and high-precision target detection. The framework reduces model complexity and inference time overhead by using a multi-input single-output approach.
Researchers can now study microplankton at an individual level using holographic microscopy and AI, gaining a deeper understanding of their movement, growth, reproduction, and interactions. This breakthrough provides new insights into the ocean's oxygen production and carbon cycle.
The 13th Annual Meeting on Skin Challenges 2022 will address key skin ageing and challenges such as skin microbiome, cancer, inflammation, wound healing, and more. The event will feature experts from industry and academia presenting their research on these topics.
A Mayo Clinic study found that clinicians who were high adopters of an AI-enabled clinical decision support tool were twice as likely to diagnose low left ventricular ejection fraction as those who were low adopters. The tool's accuracy was critical in detecting serious health conditions before symptoms appeared.
Researchers used AI to predict compounds that could neutralize reactive oxygen species causing baldness. They successfully regenerated hair on mice using microneedle patches, providing a promising new treatment for androgenic alopecia.
A study of 9,303 US adults found that people with cardiovascular disease were less likely to use wearable devices, highlighting disparities in access and use. The research emphasizes the need to ensure equitable access to wearables to benefit high-risk populations.
Researchers at the University of Illinois developed an AI-powered system that uses a molecule-making machine to find optimal reaction conditions for synthesizing chemicals. The system doubled the average yield of a challenging class of reactions, paving the way for faster innovation and automation in biomedical and materials research.
Researchers aim to identify electrical activity in brain consolidation and test targeted brain stimulation to strengthen memories. The study could advance understanding of neural mechanisms involved in memory formation, potentially benefiting people with Alzheimer's disease.
An AI-based model has been developed to assist radiologists in detecting and identifying leadless implanted electronic devices (LLIEDs) on chest X-ray images. The model achieved high detection and classification accuracy, even with suboptimal image quality, and showed promise for real-world deployment.
The Beckman Institute has established a new national collaborative Biomedical Technology Research Resource to develop label-free optical imaging technologies. The center aims to create optical and computational imaging technologies that can serve as a resource for clinicians and researchers.
A study by Professor Dennis Murphy Odo found that automatic text simplification (ATS) software makes authentic materials more comprehensible for L2 learners with high reading proficiency. However, the tool's effectiveness is limited for learners with lower reading proficiencies. The researcher suggests that ATS tools need to be further...
Researchers at Purdue University and the University of Tennessee, Knoxville, have developed a metamaterial that can learn to adapt to its surroundings on its own. The material uses shape to store information in microseconds, allowing drones to quickly recall patterns associated with dangerous conditions.
Researchers aim to use quantum computer-based AI to accelerate drug discovery, cutting costs and time by exponentially increasing processing power for complex problems. Quantum AI models have higher capability to approximate desired functionality compared to classical neural networks.
Lei Yang is conducting research on developing fair AI-assisted mobile dermatology diagnosis technology using unsupervised federated learning. The goal is to ensure participation from all socioeconomic populations and find the best network while considering hardware constraints.
A new study published in iScience found that humans tend to follow a two-step process when in a crowd, with an initial reflexive imitation followed by a more deliberate strategic decision. The research suggests this influence affects not only social norms but also immediate actions and underlies behaviors such as rioting and mass panic.
Researchers at MIT have developed a new method that uses optics to accelerate machine-learning computations on low-power devices. By encoding model components onto light waves, data can be transmitted rapidly and computations performed quickly, leading to over a hundredfold improvement in energy efficiency.
Researchers developed an AI-based model that combines artificial intelligence and weather forecast models to predict extreme wildfire danger with high accuracy. The new method can produce forecasts of extreme fire danger out to one week at finer scales (4km x 4km resolution), increasing its utility for fire suppression and management.
Researchers at Indiana University have developed a virtual reality therapy to aid in substance use disorder recovery, using 'future-self avatars' to help people choose long-term rewards over immediate gratification. The technology has shown promising results in lowering relapse rates and increasing future self-connectedness.
A new AI model developed by researchers at the University of Georgia uses artificial intelligence to analyze terabytes of quail call recordings, allowing wildlife managers to gather data in a matter of minutes. The model is accurate, picking up between 80% and 100% of all calls, even in noisy recordings.
FathomNet aggregates images from multiple sources to create a publicly available, expertly curated underwater image training database. The database uses artificial intelligence and machine learning to alleviate the bottleneck for analyzing underwater imagery, accelerating important research around ocean health.
Omnipose, a deep learning software, can identify various types of tiny objects in micrographs with high precision, including bacteria of all shapes and sizes. It overcomes limitations of previous approaches by handling object overlap and detecting cell intoxication, making it a game-changer for biological image analysis.
A study found that Italian regions with high levels of environmental pollution have higher cancer mortality rates, even after controlling for lifestyle factors. The analysis identified specific sources of pollution associated with certain types of cancer, highlighting the need for environmental reduction and prevention to combat cancer.
A new study aims to diagnose severe neurodegenerative diseases like ALS and FTD with the help of speech tests. AI can analyze subtle nuances of speech patterns, including pauses, speed, and melodic aspects, to detect early changes.
Researchers found that AI language models exhibit significant implicit bias against individuals with disabilities, resulting in inaccurate sentiment analysis and potential misclassification of posts as toxic. The models' biases were apparent in various applications, including autocorrect and social media content moderation.
A new project will develop a technique to quantify uncertainty in AI-based tools used for image analysis and create a questionnaire to assess patients' risk tolerance when using these tools. The goal is to ensure that AI-assisted clinical decisions are informed by the inherent uncertainty of imaging technologies.
Researchers created living brain cells in a dish that can perform goal-directed tasks and adapt to changes, opening doors for new understanding of brain function. The study also raises possibilities for alternative animal testing and biomimetic research.
A team of researchers at the University of Pittsburgh is using artificial intelligence to create more efficient and effective organoids. By designing and printing smarter cell structures that mimic human organs, they aim to reduce trial-and-error methods and costs, ultimately contributing to new methods in disease research and human he...
Researchers from McGill University and MIT developed an AI system that can learn the rules and patterns of human languages on its own. The model automatically generates higher-level language patterns that can be applied to different languages, achieving better results.
A Cleveland Clinic-led research team created a discovery tool outlining interactions between COVID-19 and host proteins, identifying potential host-targeting therapies. The study confirmed over 200 interactions and discovered new ones, highlighting promising approaches for treating COVID-19.
Researchers at North Carolina State University developed a blueprint for incorporating ethical guidelines into AI decision-making programs. The new mathematical formula, based on the Agent, Deed, and Consequence (ADC) Model, considers intent, character, and consequences of actions to make more informed decisions.
A perspective paper explores the role of clinician-data-scientists in healthcare, emphasizing their need for interdisciplinary knowledge and training. The researchers highlight the importance of integrating data science into conventional medical education to prepare clinicians for the digital health era.
New research highlights the dangers of AI-powered recruitment tools that claim to remove discrimination from hiring. The tools reduce race and gender to trivial data points and often rely on personality analysis that is
The program cuts the average time it took for new patients to get their first treatment from 97 days to just 41 days, while also allowing more than 1,000 new patients to begin treatments. The system has made significant improvements in efficiency and patient satisfaction, with appointment no-shows dropping by 50%.
A University at Buffalo-led research team has been awarded a $5 million grant to develop digital tools that can help older adults recognize and protect themselves from online deceptions. The project, DART, aims to reduce online fraud among older adults, who lose billions of dollars each year due to scams.
A new screening test App can produce accurate results using just people's voice recordings, improving the management of Parkinson's disease and severe COVID-19. The smartphone App takes just 10 seconds to reveal whether a person may have Parkinson’s disease and should be referred to a neurologist.
A new study proposes a powerful computer-modeling approach to cell simulations, reaching unprecedented simulation timescales at all-atom resolution. The technique combines advantages of protein docking and molecular simulations, enabling faster and more precise treatment of human disease.
Researchers developed a new technique that enables on-device training using less than a quarter of a megabyte of memory, reducing the need for powerful computers and central servers. This approach preserves privacy by keeping data on the device, making deep learning more accessible for low-power edge devices.
A Rutgers-led study statistically evaluated government data to determine if COVID-19 vaccination increases the incidence of Guillain-Barré syndrome. The results show no significant association between any COVID-19 vaccinations and the disease.
The new computer chip uses a transistor-free design that eliminates data transfer time and minimizes energy consumption. It offers up to 100 times faster performance than conventional computing architectures, making it ideal for AI applications.
Physicists at the University of Basel have developed a computational shortcut for neural networks, allowing for faster calculation of optimal solutions without training. This breakthrough provides insight into neural network functioning and could help detect unknown phase transitions in materials and quantum systems.
Neuronal silencing periods enable efficient temporal sequence identification, allowing the brain to remember phone numbers and PINs. A new AI mechanism utilizing this mechanism also protects against stolen cards by recognizing personal handwriting style and timing.
Researchers developed a machine learning model to quickly recognize predictive risk factors and their importance for undesirable hospitalization outcomes. The model achieved an accuracy of 95.6% and identified modifiable risk factors that can be mitigated through clinical interventions.
Researchers at Mayo Clinic used AI to evaluate patients' ECGs, identifying new cases of atrial fibrillation that would not have been detected through routine care. The study showed that AI can target screening to high-risk patients, potentially reducing undiagnosed strokes and deaths worldwide.
Researchers have developed a scalable, fully coupled quantum-inspired processor that can solve optimization problems efficiently. The system uses an array calculator approach to divide calculations among multiple chips, reducing data transmission and increasing performance.
A recent grant will fund a project developing new hardware for machine learning, aiming to curb unsustainable energy use in AI systems. The new algorithms being developed are made available to the research community and compatible with an openly shared computing platform.
The MEMQuD project investigates quantum effects in memristive devices, which could lead to breakthroughs in AI, cryptography, and computation. Researchers analyze fundamentals and applications of quantized conductivity phenomena at room temperature.