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 at Brookhaven National Laboratory have successfully discovered new materials using artificial intelligence and self-assembly. The AI-driven technique led to the discovery of three new nanostructures, expanding the scope of self-assembly's applications in microelectronics and catalysis.
A new study from Pusan National University explores the use of collaborative artificial intelligence models in fashion design, finding that human designs offer unique originality and creativity. The researchers propose a human-AI collaborative network to produce novel designs, which can also be used as a learning tool for non-experts.
A new AI tool called Sybil has been developed to predict the risk of lung cancer for individuals with or without a significant smoking history. It uses deep-learning models to analyze low-dose chest computed tomography (LDCT) scans and provides accurate predictions for up to six years.
A $749,960 NSF grant will develop AI-powered AAC devices to improve outcomes for individuals with limited speech and language. The technology aims to reduce the burden on users and enhance their participation in education and workforce activities.
A survey of researchers and the public reveals a high percentage are in favor of proceeding with neuroscience research and brain-related information use. The general public expresses hopeful feelings about this research, while major differences exist between the two groups on ELSI topics.
Scientists have developed a new method to enhance electron-photon coupling, resulting in a hundredfold increase in light emissions. The approach uses a specially designed photonic crystal to produce stronger interactions between photons and electrons.
Researchers developed an innovative deep learning-based approach to classify epileptic seizures in near real-time, overcoming clinical limitations. The system uses action recognition with intelligent 3D cropping to distinguish between frontal and temporal lobes seizures or non-epileptic events.
A new computer program, DeepMosaic, uses artificial intelligence to detect mosaic mutations in genetic sequences. This method enables accurate detection of mosaic mutations, which cause hundreds of unsolved and untreatable disorders, including epilepsy.
The article discusses the use of Rapamycin in the context of Pascal's Wager, a philosophical framework used to justify beliefs. ChatGPT's generative pre-trained transformer model provides an exhaustive research perspective on the pros and cons of taking Rapamycin for anti-aging purposes.
Researchers found that AI-assisted colonoscopy significantly improved adenoma detection rates in patients with Lynch syndrome, detecting flat adenomas more effectively than standard examinations. The study suggests that AI-assisted real-time colonoscopy is a promising approach to optimize endoscopic surveillance for LS patients.
A new AI tool developed by Brigham and Women's Hospital improves the accuracy of time-critical pathology diagnostics during surgery. The tool, which leverages deep-learning technology, translates frozen tissue samples into high-quality images, increasing diagnostic accuracy and reducing the need for lengthy laboratory tests.
A predictive model developed by University of Groningen researchers can identify cows at risk of dystocia before insemination. The model, which uses machine learning on a large dataset, suggests that it could roughly halve the risk of calving problems.
The RITHMS project aims to enhance police forces' and customs authorities' capabilities in tackling illicit cultural trafficking with innovative technologies. The platform will utilize Social Network Analysis to identify organized criminal networks and provide valuable information to investigators.
Researchers at Drexel University used GPT-3 to spot early signs of Alzheimer's in spontaneous speech, achieving 80% accuracy. The program analyzed word-use, sentence structure and meaning from transcripts to identify characteristic profiles of Alzheimer's speech.
The UTSA-led Consortium on Nuclear Security Technologies (CONNECT) has received a five-year, $5 million grant from the U.S. Department of Energy's National Nuclear Security Administration. The program aims to educate and train the next generation of scientists and engineers in nuclear security, with a focus on underrepresented students.
Researchers created an AI platform called DystoniaBoTXNet that uses brain MRIs to identify patients who will respond to botulinum toxin treatment. The platform achieved a 96.3% accuracy rate in predicting treatment efficacy, offering clinicians a new tool for refining clinical decisions.
Researchers at Georgia Institute of Technology found that AI chatbots' positive emotional displays have no effect on customer service evaluations when the source is a bot, but improve when human agents exhibit emotions. The study suggests businesses should be cautious about equipping AI agents with emotion-expressing capabilities.
A digital detection of dementia study aims to evaluate the practical use of an AI tool for early identification of Alzheimer's disease and related dementias. The study uses a passive digital marker and patient-reported outcomes survey, which have shown potential in detecting mild cognitive impairment and reducing healthcare costs.
A recent study found that AI failed to pass a radiology qualifying examination, with an average accuracy of 79.5%. However, the researchers suggest that further training and revision could lead to improved results.
Researchers are conducting on-site surveys and generating high-resolution damage maps for 20-square-mile region affected by the Category 4 storm. The goal is to inform protection efforts and help communities recover from the disaster.
Researchers developed an AI-based neural network to detect early knee osteoarthritis from x-ray images, matching doctors' diagnoses in 87% of cases. This method could help reduce unnecessary examinations, treatments, and even knee joint replacement surgery.
The UTEP-led Computing Alliance will receive $4.8M from Google to improve diversity in computer science fields. The project aims to attract, prepare and support Hispanic students for graduate degrees, with initiatives including lab design, financial support and research collaborations.
Students from the WüSpace association are working on a project to develop intelligent sensors and algorithms for small satellites, aiming to detect dangerous approaches and prevent collisions. The project is funded by the German Space Agency and allows students to gain hands-on experience in space technology development.
Researchers at Incheon National University have developed an IoT-enabled, real-time object detection system for autonomous vehicles. The YOLOv3-based model achieved high accuracy (>96%) in detecting 2D and 3D objects, outperforming other state-of-the-art detection models.
Researchers have developed a robot capable of sorting, manipulating, and identifying microscopic marine fossils. Forabot uses robotics and artificial intelligence to automate the tedious process of evaluating foram shells and fossils.
Researchers found that longer genes are linked to longer lifespans and shorter genes to shorter lifespans, with aging causing a shift towards short genes. This imbalance leads to subtle changes in thousands of genes across various tissues, suggesting systems-level changes contribute to aging.
Researchers have developed a scaled-up version of a probabilistic computer using stochastic spintronic devices, suitable for combinatorial optimization and machine learning. The new design combines conventional semiconductor chips with modified spintronic devices, achieving massive improvements in throughput and power consumption.
Researchers explored how customers react to positive emotions from AI chatbots compared to human agents. They found that adding emotions doesn't necessarily improve service quality or customer satisfaction.
Researchers at MIT have developed a scheme for private information retrieval that is about 30 times faster than other comparable methods. The technique enables users to search an online database without revealing their query to the server, with potential applications in private communication and targeted advertising.
Researchers at FAU and industry partners aim to create a universal radio adapter for seamless and secure operations through non-cooperative indigenous 5G networks. The project aims to reduce interception, disruption, or jamming of communications over 5G networks.
A massive collaborative study using federated learning developed a model that enhances identification and prediction of boundaries in three tumor sub-compartments without compromising patient privacy. The dataset, comprising 6,314 glioblastoma patients from 71 sites globally, is the largest and most diverse ever considered.
A new AI evaluation framework, GOPHER, has been developed to assess the efficiency of genome analysis algorithms. The tool judges programs on their ability to learn genomic biology, predict patterns, handle noise, and provide interpretable decisions.
A team of researchers from the University of Pennsylvania has developed a new algorithm, metadynamics, that can navigate high-dimensional energy landscapes to find low-energy configurations. This breakthrough has the potential to revolutionize fields such as protein folding and machine learning.
Researchers at University of South Australia have developed a non-contact system to accurately measure systolic and diastolic blood pressure using AI algorithms and a camera. The system achieved 90% accuracy in readings, outperforming existing methods.
A team of researchers developed a neural network that can analyze digital biopsy images to diagnose breast cancer, identifying the presence of PD-L1 protein. The AI system outperformed human pathologists in 70% of cases, with high accuracy rates and potential for personalized medicine.
A study led by Kyoto University researchers found that AI-generated haiku poems, created without human intervention, were often indistinguishable from those penned by humans. In contrast, human-AI collaboration produced more creative works.
Researchers used AI to design and test thousands of functional group patterns on a carbon nanotube pore, finding optimal arrangements that can filter out contaminants. The study demonstrates AI's potential in developing new types of water purification membranes.
Concordia researchers identify vulnerabilities in smart inverters to cyberattacks, including reconnaissance, replay, DDoS, and Man-in-the-Middle attacks. These attacks can disrupt energy flow and create power oscillations, severely impeding microgrid functionality.
A neural network trained using a diverse dataset outperforms conventionally trained algorithms by reducing bias in artificial intelligence. The use of images from low-resource populations boosts the object recognition performance of machine learning systems.
Researchers propose six competency domains for AI use in primary care: foundational knowledge, critical appraisal, medical decision making, technical use, patient communication, and awareness of unintended consequences. These competencies aim to harness AI's potential for patient and societal benefit.
Researchers from Kaunas University of Technology and Lithuanian University of Health Sciences developed an AI-based system to evaluate the 'substitute voice' of laryngectomy patients, allowing for faster detection of pathologies. The Acoustic Substitution Voice Index (ASVI) uses acoustic parameters and artificial intelligence methods t...
Researchers at the University of Texas at Dallas have developed a computer-based platform for drug discovery using topological data analysis. The approach allows for virtual screening of thousands of compound candidates, narrowing them down to the most promising ones for laboratory and clinical testing.
The researchers have developed an AI algorithm called M3GNet that can predict the structure and dynamic properties of any material. The algorithm was used to create a database of over 31 million yet-to-be-synthesized materials with predicted properties, facilitating the discovery of new technological materials.
A new intelligent observer for Esports has been developed using a Mask R-CNN algorithm to learn from human spectating data. This approach overcomes limitations of existing automatic observers, which require extensive domain knowledge and cannot capture undefined events or changes in event significance.
A new study using artificial intelligence has found that a simple eye test can accurately predict the risk of heart disease. The researchers developed an algorithm that can analyze retinal images to assess cardiovascular health, providing a non-invasive alternative to traditional risk scores.
Researchers developed a new machine-learning framework that enables cooperative or competitive AI agents to consider the future behaviors of all agents, not just their teammates or competitors. This framework, FURTHER, uses two modules: an inference module and a reinforcement learning module, to enable agents to adapt their behaviors a...
A research team developed an optical chip that can train machine learning hardware, improving AI performance and reducing energy consumption. This innovation uses photonic tensor cores and electronic-photonic application-specific integrated circuits to speed up the training step in machine learning systems.
Chung-Ang University researchers propose a new algorithm, MR-UCB and MR-APE, to tackle stochastic multi-armed bandit problems with heavy-tailed noise distributions. The methods guarantee minimal loss for worst-case scenarios with minimal prior information.
Chugh argues that AI risk assessments raise concerns about human biases and the absence of individualized decision-making in the judiciary. She advocates for more research on AI's role in the court system, prioritizing community-driven and individualized processes.
A new research project at Aarhus University aims to develop intelligent drones that can detect ice on turbine blades, optimizing energy production and expanding market opportunities. The project has the potential to reduce energy losses by up to 80% and enable wind farms to operate in colder climates.
Researchers at Singapore University of Technology and Design (SUTD) have developed a novel phase-change key for new hardware security. The device, known as the physical unclonable function (PUF), is scalable, energy-efficient, and secure against AI attacks compared to traditional silicon PUFs.
Researchers at Oak Ridge National Laboratory have discovered genetic markers for autism, developed recyclable composites to drive the net-zero goal, and created a tool for real-time building evaluation. Additionally, they have made significant progress in growing hydrogen-storage crystals using a novel nano-reactor material.
A new AI tool helps governments decide whether to bail out a bank by predicting if the intervention will save money for taxpayers. The algorithm assesses financial implications and suggests optimal bailout strategies.
Researchers used weather radar to track bird movements and found peak roosting stages shifting earlier due to warmer temperatures. This shift may lead to a shortened pre-migratory season, impacting birds' survival during migration.
Researchers have developed wearable electronics paired with artificial intelligence to detect emerging health problems, such as heart disease and cancer, before symptoms appear. The device can perform personalized analysis of tracked health data while minimizing wireless transmission.
Researchers created a Facebook-like prototype platform, called Trustnet, where users rate posts as accurate or inaccurate before sharing. This approach showed that people effectively assess misinforming posts and share their assessments with others.
Researchers at Mayo Clinic developed an AI algorithm that accurately detects weak heart pumps using single-lead Apple Watch ECGs. The system has shown promising results, rivaling medical treadmill diagnostic tests in accuracy, and holds potential for scalable screening and prevention of heart failure.
A team of researchers used AI pattern recognition to re-analyze footprints from the Dinosaur Stampede National Monument and concluded that they were made by an ornithopod dinosaur, a herbivorous species. The results contradicted the long-held assumption of a vicious dinosaur predator.
Researchers developed an AI tool that analyzes plaque features on coronary CT scans to predict reduced blood flow, potentially reducing invasive tests. The tool could help doctors determine the next step in treatment plans and risk-stratify patients correctly.
The study developed an extended deep Q-network (EDQN)-incorporated context-based meta-RL model that can autonomously detect traffic states, classify regimes, and assign signal phases. The model outperformed existing algorithms in simulation experiments and showed adaptability to new tasks without adjusting parameters.