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 UT Austin developed AI model EvoRank to design protein-based therapies and vaccines by leveraging nature's evolutionary processes. The model identifies useful mutations in proteins, offering a new approach to biomedical research and biotechnology.
Researchers from the University of Toronto's Rotman School of Management found that campaign size, social capital, and reward options are top factors in success. Machine learning identified a sweet spot for campaign duration and reward options, with success plateauing after 50 options.
A study using machine learning to analyze patents and job task descriptions found that AI is likely to augment rather than replace many jobs. The most impacted occupations included orthodontists, security guards, and air traffic controllers.
A PSU English professor is using a grant from the National Science Foundation to study one of the world's fastest and largest supercomputers, Aurora. The research aims to answer questions about how supercomputers work, their applications in science and industry, and their impact on the US's position in scientific advancement.
A study from the University of Arkansas System Division of Agriculture has improved food quality computer predictions by using human perception data. The researchers trained a computer model to mimic human adaptation to environmental conditions, resulting in more consistent predictions under different lighting conditions.
Researchers have identified coupling design methods, composite manufacturing techniques, and future prospects for micro/nanorobots. The review explores three core functions: mobility, controllability, and load capacity, offering insights into designing high-performance MNRs.
Researchers at NJIT's Institute for Space Weather Sciences and Ying Wu College of Computing are developing an AI-powered space weather forecasting system called SolarDM. The system uses synthetic vector magnetograms to provide critical data for predicting solar eruptions, which could offer a three-day forecast horizon.
Scientists used artificial intelligence and molecular dynamics simulations to understand how enzymes fold lasso peptides into a unique structure. They identified key residues important for interaction with the substrate, enabling the design of new cyclase variants that can produce potent lasso peptides.
Researchers are developing AI technology to quantify emotions, improving emotional recognition in fields like healthcare, education, and customer service. This technology can create personalized experiences and enhance comprehension of human emotions, revolutionizing human-computer interactions and mental health assessments.
The integration of artificial intelligence in intratumoral immunotherapy can refine diagnoses, guide interventions, predict treatment responses, and adapt therapeutic strategies. This enables the enhancement of patient outcomes, including improved survival rates and quality of life.
Researchers found that large language models used in home surveillance can make inconsistent decisions about calling the police, even when videos show no crime. Models often disagreed with each other and exhibited inherent biases influenced by neighborhood demographics.
A new AI model called Crystalyze can analyze X-ray crystallography data to determine the structure of powdered crystals. The model was trained on a database of over 150,000 materials and successfully predicted structures for over 100 previously unsolved patterns.
The UC3M-Universia Chair aims to address the challenges of large tech companies' data use and create a new, transparent and fair personal data economy. Researchers will develop models and algorithms linked to AI that are interpretable and unbiased.
Two new AI institutes will harness AI to analyze vast amounts of astronomical data, accelerating discoveries and democratizing access to research. Researchers at all career levels will gain access to trustworthy AI tools, enabling them to explore the cosmos with newfound insights.
Researchers aim to advance training methodologies for superintelligent systems, ensuring they learn from imperfect and evolving data. The project seeks to develop new techniques to improve AI reliability, reduce biases, and increase accuracy.
Researchers analyzed 2 million Google Street View images to explore the utility of digital data in informing public health decision-making. They found that neighborhoods with more crosswalks had lower rates of obesity and diabetes, but no significant link was found between sidewalks and health outcomes.
CREME, a new AI-powered virtual laboratory, allows scientists to run thousands of virtual experiments with the click of a button to identify key regions of the genome. This breakthrough may lead to discovering new therapeutic targets and giving scientists access to cutting-edge technology without a real laboratory.
A new AI-based system has been shown to reduce the risk of unexpected deaths in hospitalized patients by identifying those at high risk of deteriorating health. The system, CHARTWatch, uses real-time alerts and enhanced communication between nurses and physicians to support high-quality care.
Researchers at Purdue University found that autonomous vehicles can interpret and respond to commands from passengers using large language models like ChatGPT. This technology allows the vehicle to personalize its driving to a passenger's satisfaction and take into consideration traffic rules, road conditions, and weather.
A new study by Boston University researchers found that the majority of social media posts from e-cigarette brands left out health warnings, despite a federal requirement to include them. The study used AI to analyze over 2,000 Instagram posts and discovered that only 13% complied with FDA health warning requirements.
Genethon has developed an innovative gene therapy vector that effectively targets muscle tissue while reducing the risk of liver penetration. The new capsid design uses AI predictive methodology to improve efficacy and safety, paving the way for more effective treatments for neuromuscular diseases.
Researchers at Peking University developed a dual-IMC scheme to accelerate machine learning and improve energy efficiency. The new computing scheme stores both neural network weights and inputs in memory, reducing data movement and power consumption.
Researchers at Indian Institute of Science develop a neuromorphic platform that stores and processes data in 16,500 conductance states, cutting energy consumption by a huge margin. This breakthrough could enable complex AI tasks on personal devices, transforming the development of AI tools.
Using AI and the connectome, researchers can now predict individual neuron activity in living brains. The new model predicts neural activity in response to visual input and accurately reproduces over two dozen experimental studies.
A $3.9 million grant from the National Institutes of Health supports a study on wearable sleep trackers and AI in predicting blood biomarkers of Alzheimer's disease in at-risk individuals. The research aims to create an 'early warning system' for flagging individuals with a genetic predisposition to Alzheimer's.
The study reveals that local field potential events play a crucial role in processing information, even without external stimuli. The findings offer new avenues for research, diagnosis, and treatment of brain diseases, as well as the development of AI inspired by neuroscience.
Researchers at Klick Labs developed an AI technique using vocal biomarkers to predict chronic high blood pressure with up to 84% accuracy. The study used machine learning to analyze hundreds of indiscernible vocal biomarkers, including pitch variability and speech energy distribution patterns.
A new AI model generates detailed images of cancer tissue that imitate what its staining would look like, reducing the need for resource-intensive lab analyses. The VirtualMultiplexer uses contrastive unpaired translation to create accurate virtual pictures of diagnostic tissue colorations.
Researchers used Google AI tool to map proteins' configurations and their ability to resist pressure changes, offering insights into protein design and life on other planets. The findings shed light on deep ocean life and could lead to new targets for structural and biophysical studies.
Researchers developed an AI model to detect lung disease in premature babies by analyzing their breathing patterns while sleeping. The Long Short-Term Memory (LSTM) model achieved 96% accuracy in classifying flow values as belonging to a patient with BPD or not, enabling early diagnosis and treatment.
Advanced endoscopy combined with AI and digital pathology offers a deeper understanding of inflammatory bowel diseases (IBD). This leads to more accurate diagnoses and improved patient outcomes.
Researchers at Cornell University found that integrating AI into environmental control systems can reduce energy consumption in indoor agriculture by up to 25%. By optimizing lighting and climate regulation, AI helps create an energy-efficient solution for optimal plant growth, carbon dioxide levels, and ventilation requirements.
A study found that ChatGPT performed better than trainee doctors in assessing complex cases of respiratory disease in areas such as cystic fibrosis and asthma. The chatbot's responses were also scored higher for being human-like, while Google's Bard and Microsoft's Bing performed similarly to or worse than trainees.
A deep-learning algorithm developed by astronomer David Harvey can untangle the complex signals of self-interacting dark matter and AGN feedback in galaxy cluster images. The Inception model achieved an accuracy of 80% under ideal conditions, showcasing its potential for analyzing vast amounts of space data.
Researchers Maria Eichlseder and Fariba Karimi will study keyless encryption and AI's impact on online social networks to promote fair algorithms. Their projects aim to address open problems in cryptographic systems and quantify intersectional inequality.
A new AI tool called CAR-E is being developed to provide personalized coaching conversations for medical students and residents, encouraging reflective practice and enhancing their skills. The web-based tool will use a coaching approach to prompt students to think back on their clinical encounters and knowledge gaps.
Researchers at the Florida Museum of Natural History are studying bagworms' unique life cycle and their potential to inform understanding of modern climate change. They'll also analyze fossils from ancient mammal communities affected by rapid warming, as well as use AI to model future disease outbreaks.
A team at NUS Yong Loo Lin School of Medicine leveraged an artificial intelligence-derived platform, CURATE.AI, to guide treatment for a patient with Waldenström macroglobulinemia, a rare blood disorder. The trial demonstrated substantial improvement in red blood cell levels and minimised side effects.
Researchers will investigate the psychological influence of online communications developed with artificial intelligence, including misinformation and radicalizing messages. The team aims to develop a holistic model of multi-level belief resonance that can counter foreign influence on campaigns and radicalization.
Researchers at McGill University developed AI-guided feedback systems that outperformed human instructors in teaching neurosurgical skills. The study found that expert instruction alone led to poorer surgical learning outcomes, highlighting the potential of AI to enhance learner surgical skills acquisition.
Researchers found that AI-integrated apps often struggle with mixed dishes, such as Asian cuisine, which can lead to errors in energy content calculations. Manual food-logging apps also overestimated or underestimated energy intake for certain diets, highlighting the need for improved accuracy and cultural diversity.
A study at the European Society of Cardiology Congress found that an AI-enabled digital stethoscope helped doctors identify twice as many cases of pregnancy-related heart failure compared to a control group. The tool was 12 times more likely to flag heart pump weakness, leading to better diagnosis and potentially life-saving treatment.
Artificial intelligence (AI) is set to revolutionize scientific publication by assisting editors in selecting impactful papers and reviewing manuscripts. AI will help increase the influence of journals by providing an initial 'score' for articles, making triaging faster and more objective.
A machine-learning algorithm called xFakeSci has been developed to detect AI-generated scientific articles, with a success rate of nearly 94%. The tool analyzes word patterns and bigrams to distinguish between real and fake papers, highlighting the need for comprehensive detection methods as AIs become increasingly sophisticated.
A new machine-learning model developed by a University of Arkansas student improves upon existing genotype-by-environmental interaction models, achieving higher prediction accuracy. The model uses feature engineering to process environmental data, leading to a 7% improvement in mean prediction accuracy.
A Mass General Brigham-led study found that a large language model improves the accuracy of immune-related adverse event detection, identifying additional cases not picked up by manual adjudication. The model demonstrated excellent specificity and sensitivity, opening up opportunities for collaboration among institutions.
A new algorithm, inspired by the nervous system's matchmaker, pairs drivers with riders in a way that maximizes everyone's happiness. The algorithm creates near-optimal pairings while preserving privacy, making it suitable for everyday applications.
Researchers at Heidelberg University developed an AI-supported method to map mosquito populations by analyzing satellite and street view images. This approach helps assess environmental conditions favoring Aedes aegypti presence, enabling targeted disease control measures.
Researchers developed a tool to improve data transparency in large language models, enabling practitioners to find suitable datasets for their models. The tool, Data Provenance Explorer, automatically generates summaries of dataset creators, sources, licenses, and allowable uses.
Researchers aim to develop a voice assistant delivering customized cognitive stimulation therapy to improve the quality of life for persons living with dementia and their care partners. The project has the potential to positively impact a large population, including those in remote areas.
A new automated scoring system using deep learning and pyramid sampling analyzes morphological features at various spatial scales to enhance the accuracy of HER2 assessment. The system achieved a classification accuracy of 84.70% in blind testing, comparable to experienced pathologists.
A team of researchers created RENAISSANCE, an AI-based tool that simplifies the creation of kinetic models to accurately depict metabolic states. The tool successfully generated models that matched experimentally observed metabolic behaviors in Escherichia coli, simulating how the bacteria would adjust their metabolism over time.
A study by Dr. Shunichi Kasahara found that levels of identification with one's face remain consistent regardless of agency or control over facial movements. The results suggest that a sense of agency does not significantly impact our ability to judge our facial identity, even in scenarios like deepfakes.
The Human AugmentatioN via Dexterity (HAND) center aims to develop robots capable of enhancing human labor through engineered systems of dexterous robotic hands, AI-powered fine motor skills, and human interface. The center's goal is to make robotic assistance accessible and applicable to a wide range of physical actions.
Researchers found that students who struggle with executive functioning (EF) skills perceive generative AI chatbots as significantly more useful for schoolwork. Using these tools critically can support students with EF challenges, but responsible use is crucial to maintain academic integrity.
Researchers found that large language models (LLMs) can improve systems that detect bots by outperforming state-of-the-art systems by 9%. However, LLMs can also reduce the performance of existing detectors by up to 30% when used to evade automated detection.
A new course launched with funding from the UK Space Agency to address the growing skills gap in software, data, and AI for the UK space sector. The Securing the future of space: Space Software and Data/AI CPD programme will equip mid-career professionals with expertise in AI and data-science.
Researchers at the University of Illinois have developed a method to understand and improve light-harvesting molecules for solar energy applications. By combining AI with automated chemical synthesis and experimental validation, they were able to produce molecules four times more stable than traditional ones.
A new study published in Scientific Reports confirms a linear relationship between blood glucose levels and voice fundamental frequency, suggesting potential for voice-based glucose monitoring. Researchers at Klick Labs used vocal biomarkers and AI to detect Type 2 diabetes with high accuracy.
Researchers have made a significant breakthrough in vasculitis research using AI-powered big data techniques, enabling more precise identification of disease patterns. The study offers new insights into the diagnosis and treatment of systemic vasculitis, a group of rare autoimmune diseases.