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.
The African Engineering and Technology Network has signed its ninth university partner, Universidade Agostinho Neto. The network, led by Carnegie Mellon University Africa, aims to promote pan-African digital growth through research, education, and entrepreneurship.
A new AI tool developed by University of Missouri researchers can predict the 3D shape of chromosomes inside individual cells, providing a new view of how genes work. The tool helps identify unique differences in chromosome folding between cells, which controls gene activity and can lead to diseases like cancer.
A recent study evaluates GPT-4's performance in solving letter-string analogies, a task requiring basic counting and relational understanding. The model excels at this task, demonstrating emergent analogical reasoning capabilities that may be supported by structured operations and relational representations.
The study identified four simple ways music learning technology can aid prospective musicians, including helping people improve recall while listening and replaying notes indefinitely. Researchers found that existing digital learning tools were not being used effectively by students despite their availability.
Aerial robots are limited to manipulating rigid objects, but Lehigh University researcher David Saldaña aims to expand their capabilities with an adaptive controller and reinforcement learning. His research has potential applications in construction, disaster response, and industrial automation.
Researchers from Empa developed machine learning algorithms to optimize laser-based manufacturing techniques, reducing preliminary experiments by two-thirds. They also implemented real-time optimization using field-programmable gate arrays (FPGAs) for improved welding processes.
A new study investigated people's moral judgments on euthanasia decisions made by AI and robots compared to human doctors. The research found that people generally prefer decisions made by humans over AI in end-of-life care situations.
An experimental study found that humans are less likely to exhibit fairness, trust, and cooperation when interacting with a large language model (LLM) compared to another human. Participants in online games played with either a human or an LLM acting on behalf of another person showed reduced social behavior.
The ERQA framework uses a semantic vector database and curated literature repository to improve medical knowledge discovery, achieving high retrieval accuracy in literature-based QA and abstract summarization. The researchers plan to further improve the model by incorporating larger-scale biomedical literature datasets.
Researchers from The University of Osaka have demonstrated that vision transformers can spontaneously develop human-like visual attention patterns without specific training. This breakthrough showcases the potential of self-supervised learning for advancing AI applications and modeling biological vision.
The Stuttgart Cluster of Excellence IntCDC will continue to develop innovative construction methods that reduce resource consumption and CO2 emissions through computational design and engineering methods. The cluster aims to evolve its Co-Design approach into a Co-Agency approach, focusing on bio-based building materials, AI technologi...
UT-Battelle has donated $225,000 to purchase advanced manufacturing equipment for Oak Ridge High School's Wildcat Manufacturing iSchool program. The equipment includes AI- and robotics-assisted manufacturing systems, enabling students to earn college credit while gaining experience with the latest innovations in intelligent manufacturing.
Researchers at UC San Diego develop new approach using artificial intelligence to predict therapy outcomes and match patients with right treatments, improving cancer care and patient outcomes.
Aurora, a state-of-the-art machine learning model, delivers high-quality forecasts for key environmental systems like air quality, weather, and tropical cyclones. The model's flexibility enables it to be used for various future scenarios, including flood risks, wildfire spread, and renewable energy output.
Researchers at UCSF have successfully engineered a shapeshifting protein that can change shape in response to signals, potentially leading to breakthroughs in medicine, agriculture, and environmental applications. This achievement marks the first step towards creating stable yet dynamic proteins using AI-augmented protein engineering.
A team of researchers from UNIGE and UniBE used generative AI to assess emotional intelligence, finding that AIs achieved significantly higher scores than humans. The results also showed that AIs can generate new emotional intelligence tests in record time.
The ENABLE-6G project has developed 20 technological breakthroughs that prioritize network intelligence, energy efficiency, localization, and privacy-preserving analytics. The project has generated a range of outputs, including real-world testing platforms, wireless sensing algorithms, and AI-driven network optimization methods.
While digital and artificial intelligence-based pathology (DAIP) offers improved diagnostic accuracy and equity, its implementation is hindered by financial constraints, technical challenges, and legal/ethical concerns. A balanced assessment of the benefits and pitfalls must be conducted before adopting DAIP.
Derek Leben's book 'AI Fairness' offers a philosophical framework to evaluate and mitigate biases in AI algorithms. The author argues that principles like autonomy, equal treatment, and equal impact should guide the design of fair AI systems.
University of Missouri researchers create digital sentiment map using AI to analyze public Instagram posts, linking emotional tone to real-life features. The tool aims to improve city services, identify areas of concern, and inform emergency response decisions.
Triboelectric and piezoelectric nanogenerators convert mechanical energy into electrical energy, enhancing robotic autonomy and efficiency. The technology has the potential to reshape future robotic capabilities, particularly in industrial automation, healthcare, and smart home applications.
OneCareAI applies AI and supercomputing to detect early stroke risk from ECG data obtained with smartwatches, offering a non-invasive solution for personalized risk assessments. The technology has the potential to be extended to other cardiovascular diseases, opening opportunities for scalability.
A new study reveals that fine-tuned large language models (LLMs) greatly improve error detection in radiology reports, outperforming other NLP tools. The LLMs successfully identify various types of errors, including transcription and directional mistakes, providing a promising solution for medical proofreading.
A new study by the University of South Australia found that using AI alone in hiring decisions does not necessarily lead to more diverse and inclusive outcomes. The research highlights the importance of organizations having clear diversity guidelines, qualitative goals, and human oversight to support the use of AI tools effectively.
The application of AI in public health informatics offers potential to revolutionize data collection, disease surveillance, decision-making, and interventions. However, its implementation faces technical, ethical, and operational challenges related to health equity, privacy, security, and bias.
Rice University will offer a Bachelor of Science in artificial intelligence beginning in the fall of 2025. The new major provides a cohesive program covering various approaches to AI and incorporates disciplines outside of engineering.
The National Heart Centre Singapore is launching a nationwide AI initiative to reduce hours of specialist analysis for cardiac scans from minutes, aiding early detection and prediction of coronary artery disease. The SENSE project will apply advanced machine learning technology to interpret cardiac imaging scans.
Researchers found that artificial intelligence tools can accurately predict disease for patients with typical symptoms but struggle with those exhibiting atypical symptoms. Human oversight is necessary for high-quality patient-centered care when using AI as an assistive tool.
A survey of 3,000 US residents found that Americans prefer domain experts over non-experts or algorithms for content moderation. Small juries of independent experts were viewed as the most legitimate, while large, diverse juries with minimal qualifications were also seen as acceptable.
Researchers at KAIST have developed an AI-powered app called AACessTalk that enables meaningful communication between children with autism and their parents. The app uses personalized vocabulary cards and customized prompts to foster mutual engagement in dialogue.
The article highlights key pitfalls in evaluating AI algorithmic biases in radiology, such as the lack of representation in medical imaging datasets and inconsistent demographic definitions. To address these issues, radiologists recommend collecting and reporting more demographic variables and establishing standard notions of bias eval...
DeepSeek-R1 has been shown to enhance clinical workflows, supporting diagnostic reasoning, treatment planning, and risk assessment. The model has also demonstrated promise in patient engagement and medical education, improving patient adherence and creating interactive educational cases.
Neurosymbolic AI proposes an alternative model that requires less computing power, allowing smaller players to enter the field. This approach enables efficient and trustworthy AI systems without unsustainable energy use or gatekeeping.
Training neural networks on simple cognitive tasks improves their ability to handle more complex ones. By adopting the principles of early childhood education, researchers found that recurrent neural networks can be trained faster and with better results.
Researchers at Duke University developed a novel framework called WildFusion that fuses vision, vibration and touch to enable robots to sense complex outdoor environments like humans do. The system was tested in real-world settings and showed remarkable ability to accurately predict traversability and improve robot decision-making.
The AI system uses evolutionary computing to find optimal policy solutions that balance trade-offs between carbon storage, economic disruptions, and environmental benefits. It recommends nuanced approaches to land-use strategies, such as replacing crop land with forest, rather than simply converting all land into forests.
A team of scientists simulated the movement of microorganisms in liquids without a central control system. They found that simple rules and decentralized control can lead to efficient swimming behavior, potentially enabling nanobots to transport drugs or perform other complex tasks.
A deep learning model called Sybil can predict future lung cancer risk from a single low-dose chest CT scan. The model demonstrated good performance in predicting cancer diagnosis at both one and six years, including in never-smokers.
A new wearable sensor has been shown to effectively monitor obstructive sleep apnea (OSA) treatment response, offering a bridge between consumer wearables and medical devices. The device provides continuous data collection and connects to an app for patients and healthcare providers to share information and make informed decisions.
A team of San Diego researchers is developing an innovative AI tutor system to provide personalized support to students. The system, based on large language models, will be deployed in eight foundational courses at higher education institutions in San Diego County and assessed for its impact on learning.
Researchers created over 3,800 anatomically accurate digital hearts to investigate how age, sex, and lifestyle affect heart disease. They found that age and obesity cause changes in the heart's electrical properties, which could explain why these factors are linked to a higher risk of heart disease.
Researchers at Virginia Tech have designed a new metallic material alloy with superior mechanical properties, leveraging data-driven frameworks and explainable AI. This breakthrough accelerates the discovery of advanced metallic alloys, offering insights into materials' structure-property relationships.
A new special report warns of LLM cybersecurity threats in radiology, highlighting the importance of implementing security measures to prevent malicious use. The report recommends robust security measures and best practices for safe integration of LLMs into healthcare.
Researchers propose Input-Driven Plasticity model, which integrates past and new information to guide memory retrieval. The model is robust to noise and uses it as a means to filter out less stable memories.
Researchers found that vision-language models fail to understand negation words like 'no' and 'not', which can cause incorrect diagnoses. This limitation affects multiple choice question answering with negated captions, with accuracy dropping below random chance.
A new AI-driven tool can forecast acute child malnutrition in Kenya up to six months in advance with high accuracy, enabling timely interventions. The model integrates clinical data and satellite information to identify emerging risk areas, providing a game-changing solution to address public health emergency in the country.
The new Jean Zay supercomputer in France has increased its AI dedicated resources fourfold to 125.9 petaflops, offering free access for thousands of research projects and start-ups. The upgraded machine is expected to accelerate French and European power in artificial intelligence.
UCF students created an AI system, AIMS, to track surgical staples during robotic surgeries, reducing waste and improving sustainability. The technology was developed as part of the college's Senior Design capstone course and has been successfully tested in operating rooms at Orlando Health.
A study suggests that groups of artificial intelligence language models can self-organise into societies, reaching consensus on linguistic norms, and are prone to tipping points in social convention. Collective biases emerge between agents through interactions, a blind spot in most current AI safety work.
New York University researchers developed a novel process using machine learning to reveal groups of genes governing nitrogen use efficiency in plants like corn. The study aims to help farmers improve crop yields and minimize fertilizer costs.
JMIR Mental Health is seeking rigorous research on AI-powered therapy bots and virtual companions for mental health. The journal aims to explore their effectiveness, limitations, and place within broader care models.
A new deep learning model, ENDNet, significantly enhances subgraph matching accuracy by identifying and neutralizing extra nodes that interfere with the matching process. This improves performance in pattern recognition tasks across various fields, including drug discovery and natural language processing.
A study analyzing clinical notes found stigmatizing language was more common in Black patients' charts, with 54.9% experiencing bias. Hispanic and Asian/Pacific Islander patients also showed disparities in documentation, highlighting the need for culturally sensitive practices in perinatal care.
A new study uses explainable machine learning to predict metastasis and mortality in children with medulloblastoma, identifying key immune factors driving risk. The model provides a transparent approach to prognostic accuracy and supports personalized clinical decision-making.
A new AI model can predict protein location in human cells with high accuracy, enabling faster diagnosis of diseases like Alzheimer's and cancer. By combining protein sequence analysis with computer vision, the model can pinpoint proteins' locations at the single-cell level.
Researchers, Mollie Brewer and Kevin Childs, are exploring how coaches use data and technology to maximize player performance and safety. They found that coaches analyze data from wearable sensors to determine when players need rest or additional training, and that AI-powered analytics can improve team strategy.
A study found that large language models generalize language patterns in a surprisingly human-like way through analogy, relying on stored examples and drawing analogies when dealing with unfamiliar words. The models behave as if they have formed a memory trace from every individual example of every word encountered during training.
Researchers developed an AI system called Image2Reg that can identify genetic perturbations in cell images, potentially leading to new drugs. The system uses machine learning and molecular networks to analyze patterns in chromatin structure, revealing links between genes and their functions.
A new AI-based method accurately sorts cancer patients into groups with similar characteristics before treatment and similar outcomes after treatment. The approach showed better performance than standard statistical and machine learning methods in predicting treatment outcomes from health record data.
New AI tools are preserving marginalized cultures by recording endangered languages, creating interactive learning tools, and preserving oral histories. The authors highlight the importance of culturally aware AI systems that can adapt to regional traditions and perspectives.