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 developed a personalized brain stimulation system powered by AI to safely enhance concentration from home. The system, which uses non-invasive brain stimulation and adaptive AI, showed significant improvements in sustained attention and learning abilities.
Experts suggest a clear separation of roles between AI systems and radiologists to overcome challenges such as cognitive biases and misaligned incentives. A framework for role separation is proposed, including three models that can be adapted to specific needs, enabling institutions to implement hybrid approaches.
Lydia Kavraki, a pioneering researcher in robotics and AI, has been elected to the European Academy of Sciences. Her work on physical AI, transforming robotics and biomedicine, and leadership at Rice University's Ken Kennedy Institute have earned her this prestigious honor.
Researchers create a technique to model organic objects, creating photorealistic 3D images of complex shapes for autonomous sorting. This method improves robotic systems that sort microscopic marine fossils used in climate research.
Researchers developed drones that can safely explore air ducts by understanding airflow patterns and stabilizing their position using lasers and AI. The study opens up new application domains for drones in industrial inspection and public safety.
The National Science Foundation has awarded the University of California, Davis a $5 million grant to develop an Artificial Intelligence Institutes Virtual Organization (AIVO), a community hub for AI research and education. The new hub will provide events, venues, and partnerships to promote cross-institute connections and foster posit...
Brown University researchers will lead a national institute focused on developing AI assistants capable of trustworthy, sensitive and context-aware interactions with people. The goal is to create AI systems that can interpret a person's unique behavioral needs and provide helpful feedback in real time.
A new study reveals that pedestrians are now walking faster and spending less time in public spaces. Researchers analyzed 40 years of video footage to find a 14% decline in people lingering in these areas.
New research highlights the transformative power of digital technology in shaping the e-patient era, enabling active participation and co-production in healthcare. Key technological innovations have built upon each other, providing patients with unprecedented tools for self-care and interaction with the healthcare system.
Researchers at NTU Singapore have developed an AI-powered robotic system to assemble cyborg insects for search and rescue efforts, significantly reducing preparation time and human error. The automated system can attach electronic backpacks to Madagascar hissing cockroaches in under 8 minutes, about 30 times quicker than manual methods.
Mayo Clinic has deployed NVIDIA Blackwell infrastructure to accelerate pathomics, drug discovery, and precision medicine using generative AI. The new infrastructure enables faster pathology slide analysis and foundation model development, reducing work time from four weeks to one week.
A new blood test leverages AI to identify Lyme disease sooner and more accurately than current standard tests, with sensitivity and specificity over 90%. Additionally, an AI tool, Medicine-GPT, demonstrates promise in helping adolescents gather useful medical information, outperforming ChatGPT-4 on completeness and helpfulness.
Researchers at the University of Rochester are developing biologically inspired predictive coding networks for digital image recognition using analog circuits, which could lead to more efficient drones. The team aims to approach the performance of existing digital approaches and translate it to complex perception tasks needed by self-d...
A machine learning model accurately predicted no-shows and late cancellations in primary care practices, with the gradient boost model achieving 85% accuracy for no-shows and 92% for late cancellations. Patient characteristics such as sex, age, and socioeconomic status played a significant role in missed appointments.
A team of computer scientists created 2,300 original sudoku puzzles and asked AI tools like OpenAI's ChatGPT to solve them. The results showed that while some AI models could solve easy sudokus, most struggled to provide accurate explanations, raising questions about the trustworthiness of AI-generated information.
Six UNH faculty members receive prestigious CAREER grants to develop innovative technologies addressing pressing global issues. The recipients' projects focus on climate resilience, artificial intelligence, software reliability, and healthcare technologies, aiming to improve public safety and well-being.
A new framework developed by Northwestern University and UCLA scientists integrates various water-related processes with a machine-learning model to predict landslide threats. The framework identifies three main pathways leading to landslides: intense rainfall, rain on already saturated soils, and melting snow or ice.
A special issue examines how AI can support human flourishing in various contexts, including healthcare, education, and digital interactions. The issue highlights the need for humane AI that balances technological advancement with human-centric values and psychological insight.
A new AI model called RiboNN predicts translation efficiency of mRNA sequences, accelerating the development of mRNA therapeutics. The tool helps predict how much protein cells will produce, minimizing trial-and-error experimentation.
The team aims to deliver AI power directly to devices, improving resilience and speed in constrained environments. By processing data step-by-step across a network of devices, they can create a safe and adaptable system that can withstand attacks and extreme conditions.
Two research teams will use AI to advance screening and treatment for cardiovascular disease, a leading cause of death in the US. The projects aim to improve health outcomes and save lives by detecting early signs of kidney and liver disease, as well as personalizing CPR techniques.
A new robotic slip-prevention method has been developed to improve robots' grip and handling of fragile or slippery objects. This bio-inspired approach allows robots to predict when an object might slip and adapt their movements in real-time, outperforming traditional strategies.
Researchers use AI to solve differential equations, such as Schrodinger's equation, for large-scale systems, improving efficiency and accuracy in fields like drug discovery and material design.
Researchers found that ChatGPT-4 performed better across demographic groups, while LLaVA showed significant sex-related biases in diagnosing skin diseases from medical images. The study emphasizes the need to address these biases to ensure AI models are safe and effective for all patients.
A study published in PLOS One found that AI-generated music triggered greater physiological responses and was perceived as more emotionally stimulating compared to human-created music. The complexity of the prompt used also affected the impact of the music, with more complex prompts causing higher cognitive loads.
Answer ALS is launching a groundbreaking collaboration with Tulane University and the Pennington Biomedical Research Center to harness AI for ALS treatment discovery. The Louisiana AI Drug Development Infrastructure for ALS (LADDIA) will prioritize therapeutic targets using AI-driven insights from the Answer ALS' Neuromine Data Portal.
A novel AI-powered flood damage assessment using satellite imagery has been developed, achieving 74% of fully supervised performance with just 10% labeled data. The Simple Prior Attention Disaster Assessment Net (SPADANet) model improves recall by over 9% compared to existing models.
Researchers at the University of Waterloo have created a tool called UnMarker that can remove any AI image watermark, highlighting the vulnerability of this technology to deepfakes. The team's discovery shows that even invisible encoded watermarks can be destroyed without knowing their design or internal parameters.
Researchers developed an AI-based screening tool using pangrams to detect Parkinson’s disease with nearly 86 percent accuracy. The web-based test analyzes voice recordings for subtle patterns linked to the neurodegenerative disease, identifying potential warning signs.
A global research team developed an AI model that can predict the death risk of hospitalized liver patients with cirrhosis, outperforming older methods. The model uses advanced machine learning tools to identify key risk factors, allowing healthcare providers to intensify care and make informed decisions.
Researchers developed an AI tool to automatically generate HIV prevention and testing campaign messages for counties in the US, leveraging real-time social media data. The method was tested in three studies, showing that AI-selected messages were perceived as more actionable and effective by target audiences than control messages.
A University of Kansas study found that people rate corporate crises messages written by humans as more credible and trustworthy, regardless of the approach taken. However, the approach itself didn't vary between participants who read human or AI-written content.
CORNETO enables researchers to extract molecular networks by combining experimental data with prior biological knowledge, helping to better understand cell health and disease mechanisms. The tool identifies shared pathways and patient-specific differences, a step toward personalised treatment strategies.
Research combines AI-generated disinformation with the repetitive truth effect to create persuasive content. A study found that while neither tactic convinced participants of conspiracy theories, AI-generated disinformation increased perceived consensus among both parties.
The lab utilizes AI to automate and accelerate nuclear license applications, reducing review times by approximately 90% compared to traditional methods. This innovation aims to improve the efficiency of the licensing process while maintaining safety standards.
A new UNLV-led study uses AI to detect emerging virus variants in wastewater samples, outperforming existing methods. The algorithm can identify unique signatures for different virus variants with as few as two to five samples, significantly earlier than current methods.
Researchers developed an AI model that accurately differentiates patients with various neurodegenerative disorders using 3D brain imaging data. The model achieved high accuracy, particularly for vascular dementia and Alzheimer's disease, by focusing on subcortical brain structures.
Researchers developed CoSyn, a new approach to train open-source models using AI-generated scientific figures and charts. The resulting dataset, CoSyn-400K, includes over 400,000 synthetic images and 2.7 million sets of corresponding instructions. CoSyn-trained models match or outperform proprietary peers in various benchmark tests.
Researchers propose adaptations to overcome barriers to the implementation of autonomous AI agents in healthcare, including extending enforcement discretion policies and developing voluntary alternative pathways. Long-term solutions include regulating AI agents like medical professionals, with structured training processes for autonomy.
The study explores the technological evolution of surgical robots and their current clinical applications. Surgical robots have addressed challenges in operating within small anatomical spaces, improving medical efficiency, but also increasing costs and complexity of operations.
Researchers found that deep neural networks exhibit absorbing phase transitions, a phenomenon observed in physical systems like forest fires. This discovery provides a unified framework describing how the signal propagates between layers of neurons, enabling prediction of trainability and generalizability.
The review proposes a systematic AI-driven framework for OLED material design, offering theoretical guidance and practical pathways for intelligent materials development. Machine learning models are used to predict core optoelectronic properties, enabling rapid and accurate property prediction while providing structural insights that g...
MIT engineers developed a versatile demonstration interface that allows users to teach robots new skills in three intuitive ways: remote control, physical manipulation, or demonstration. This innovation expands the type of users and 'teachers' who interact with robots, enabling robots to learn a wider set of skills.
A study on public perception of physicians who use AI found that while effects are relatively small, they may be highly relevant due to the close link between trust in healthcare practitioners and subjective treatment outcomes. The integration of AI in healthcare has sparked certain reservations among the public.
Researchers used an AI model to reassess a completed clinical trial for an Alzheimer's disease drug, finding it slowed cognitive decline by 46% in early-stage patients. The AI model predicts patient progression and allows for more precise selection of trial participants, potentially reducing the cost of developing new medicines.
ADLM 2025 will tackle urgent topics like clinical AI integration and fake medical news, as well as leveraging genomics for personalized healthcare. The meeting also explores the health threat of plastics and microbiome medicine to combat diseases.
The new compute roadmap aims to improve lives and livelihoods with advanced computing power. It includes investments in AI research, healthcare diagnostics, and renewable energy.
A new poll suggests that older adults are divided on the use of artificial intelligence (AI), with some expressing curiosity and others skepticism. The study found that nearly all participants wanted clear labeling of AI-generated information, while also acknowledging its potential benefits for independent living. However, many express...
CodeSteer, a smart coach developed by MIT researchers, guides large language models (LLMs) to switch between text and code generation to solve complex problems. The system boosts the accuracy of LLMs on symbolic tasks like scheduling shipments in supply chains and multiplication problems.
A NUS-led global study reveals that 30-minute functional MRI scans deliver up to 22% in cost savings while retaining or improving prediction accuracy. This finding could reshape how researchers design neuroscience and mental health studies, especially for hard-to-recruit populations.
Scientists use human-AI collaboration to tackle complex questions in condensed matter physics, leveraging machine learning algorithms to identify patterns in simulation data. This approach successfully models the behavior of frustrated magnets and sheds light on quantum computing and gravity.
Researchers from the Weizmann Institute of Science and Intel Labs have developed new algorithms that allow AI developers to combine the power of different AI models, speeding up large language model performance by 1.5-2.8 times. This enables faster collaboration between models, reducing processing power costs and improving overall effi...
A new approach by MIT researchers allows scientists to efficiently estimate how combinations of treatments will affect a group, enabling fewer costly experiments while gathering more accurate data. The framework considers the scenario where all treatments are assigned in parallel and controls the outcome by adjusting treatment rates.
The Idaho National Laboratory is using Microsoft's Azure cloud and artificial intelligence to automate the nuclear permitting and licensing process. The tool generates reports required for construction permits and operating licenses, streamlining efficiency and accelerating deployment of advanced nuclear technologies.
Researchers created an 'encyclopedia of sugar utilization pathways' in 263 Bifidobacterium genomes. This resource helps predict which strains thrive in different conditions, enabling personalized probiotics to match children's lifestyles and dietary needs. The study suggests a potential solution to improving outcomes for preterm infants.
Researchers have developed a groundbreaking technique that maps temperature in three dimensions within biological tissue using invisible light and artificial intelligence. This new technology has the potential to improve early disease detection and treatment monitoring without the need for costly or invasive imaging technologies.
Georgia Tech is building a new artificial intelligence-centered supercomputer called Nexus, which will integrate cutting-edge hardware and software services to unify scientific research workflows. NCSA is lending its expertise to assist in the development of this national-scale computational resource.
Researchers from Memorial Sloan Kettering Cancer Center developed a new approach to induce mutations in resistant cancer cells, making them sensitive to immunotherapy. The study showed positive outcomes in patients over 90 with lung cancer who underwent surgery.
A new deep learning model enhances handheld 3D medical imaging by automatically tracking transducer motion without external sensors. The model produces more realistic 3D US images and can reconstruct blood vessel structures using ultrasound and photoacoustic data.
An AI model accurately detected tumor locations and outperformed benchmark models in detecting breast cancer, according to a study published in Radiology. The model learned a robust representation of benign cases to better identify abnormal malignancies, even with underrepresented data.