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 used machine learning to identify 'synthetic extreme' DNA sequences that are active in humans but not fruit flies. These rare sequences have potential practical applications in biotechnology and biomedical research.
Researchers found that individuals with high expectations of AI and brain-computer interfaces take greater risks despite no actual improvement. Expectations-based decision-making can lead to negative consequences, emphasizing the need for accurate evaluation and validation of new technologies.
Researchers developed AI model QUADL that can create online assessment questions indistinguishable from human-written ones. Instructors found QUADL's questions as effective as those written by humans in assessing student learning objectives. The study suggests QUADL can be a useful tool for instructors and course developers.
Researchers propose a four-step process for guiding the use of ChatGPT in education, identifying desired outcomes, determining automation levels, ensuring ethical considerations, and evaluating effectiveness. The study finds that ChatGPT can improve teaching models, assessment systems, and student learning experiences.
A study found that a conversational artificial intelligence program can generate easy-to-understand, scientifically adequate answers to common patient questions about colonoscopy. The program outperformed human ratings in terms of scientific adequacy and satisfaction with the answers.
A new machine learning-based model predicts individual cardiac surgery patient mortality risk with improved performance over current population-derived models. The model uses electronic health records to provide personalized risk assessments, offering a significant advantage over existing benchmarks.
A new pilot study led by University of Illinois Chicago researchers found that an AI voice-based virtual coach improved depression and anxiety symptoms, as well as problem-solving skills, in patients. The Lumen app delivered a form of psychotherapy, resulting in changes in brain activity and reduced psychological distress.
Large language models like ChatGPT show incredible potential in radiology, but also struggle with reliability and accuracy. The latest model GPT-4 improves advanced reasoning capabilities and performs better on higher-order thinking questions.
The National Institutes of Health is enrolling 10,000 participants in a landmark precision nutrition study. The study aims to develop algorithms predicting how individuals respond to different foods and diets based on genetic, lifestyle, and environmental factors.
A diagnostic study involving 16 radiologists and 2,054 images suggests that optimized AI strategy reduces diagnostic time-based costs without sacrificing accuracy for senior radiologists. Traditional all-AI strategy may still be more beneficial for junior radiologists.
Researchers at the University of Waterloo have developed a robot system that uses artificial intelligence to track objects, including medication and glasses. This technology has shown high accuracy in locating everyday items, potentially improving the quality of life for individuals with dementia.
Researchers developed an AI-powered tool to identify and measure coral reef halos globally, providing a new method for monitoring ecosystem health. The tool enables efficient tracking of reef ecosystems' function at large scales, improving understanding and management of coral reefs.
A new artificial intelligence algorithm, SSAFS, uses handcrafted image features for accurate plant disease detection and severity estimation. The algorithm outperforms existing state-of-the-art algorithms in identifying valuable disease-related features.
An AI developed at TU Wien has shown to suggest appropriate treatment steps in cases of blood poisoning, outperforming human decisions. The AI can examine time-varying patient conditions and calculate treatment strategies, increasing cure rates by up to 3%. However, legal aspects and liability need discussion.
Researchers found that machine-learning models trained with descriptive data label rule violations more harshly than humans, leading to potential serious implications in the real world. This study highlights the need for careful consideration of data labeling and training methods to ensure fairness and accuracy in AI decision-making.
Researchers found that highly work-relevant personal information from an AI agent elicits greater empathy in users, while less or no disclosure leads to suppressed empathy. This study suggests self-disclosure could be used to improve people's acceptance of AI technologies.
A team of researchers has developed an AI tool called CRANK-MS that uses neural networks to analyze biomarkers in patients' bodily fluids and predict Parkinson's disease onset with an accuracy of up to 96%. The tool may help identify early warning signs for the disease, which can be challenging to diagnose.
Researchers used AI to study how the hippocampus produces varied replay types efficiently and their purpose. The model showed that sequences are prioritized stochastically according to familiarity and reward positions.
A team of researchers developed an unsupervised entity alignment framework to improve knowledge graph search, avoiding human labor. The framework outperformed most competitors on precision and recall, scoring higher overall across multiple datasets.
The article highlights the risks of AI misuse, including its impact on democracy, job loss, and social division. Experts warn that self-improving AGI poses an existential threat to humanity, and call for regulation to minimize harm and maximize benefits.
Researchers used large language models to generate open-ended answers, which were often more convincing than real responses. This approach may help gather data quickly and at low cost but also raises concerns about the authenticity of online user data.
Researchers used AI tools to simplify a test for hepatitis C and SARS-CoV-2, achieving 97% accuracy for SARS-CoV-2 and 95% accuracy for the most prevalent version of hepatitis C. The team plans to refine the test, improve its ability to distinguish between strains, and potentially develop at-home tests in the future.
Researchers developed EmbryoNet, an automated image analysis software that uses AI to detect and classify developmental defects in fish embryos. The software outperforms human experts in terms of speed and accuracy, making it a valuable tool for investigating the mechanisms of drug action and studying embryonic development.
Researchers developed an online adaptive model for streaming anomaly detection that incorporates human-machine cooperation. The ISPForest method adjusts parameters and structures in real-time based on human feedback, leading to improved accuracy and reduced labor costs.
Researchers from Integrated Biosciences developed an AI platform to discover novel senolytic compounds, a class of molecules targeting age-related processes. The platform identified three highly selective and potent compounds with favorable medicinal chemistry properties.
Researchers have developed a new method called EvoAug that uses artificial DNA sequences inspired by evolution to train deep neural networks for genome analysis. This approach enables the model to recognize regulatory motifs more accurately, leading to better performance and potential breakthroughs in understanding human health.
A diagnostic study using 4,095 retinal fundus images found that biomarker-based AI algorithms can be susceptible to racial bias, even when trained on raw images. This issue highlights the need for careful evaluation of AI performance in diverse populations.
The UMD-led TRAILS institute will develop AI technologies that promote trust and mitigate risks through broader participation, new technology development, and informed governance. The institute aims to create AI systems that align with values and interests of diverse groups, leading to increased transparency, reliability, and accountab...
Researchers have developed a system that uses generative diffusion to create new proteins, advancing the field of generative biology. The system, called ProteinSGM, learns from image representations to generate fully new proteins, which are biophysically real and functional.
The National Science Foundation has awarded Columbia University a $20 million grant to establish the AI Institute for Artificial and Natural Intelligence (ARNI), an interdisciplinary center focused on connecting AI systems to brain research. ARNI will bring together top researchers from across the U.S. to advance neuroscience, cognitiv...
Three high school students co-authored a paper using AI engine PandaOmics to discover new therapeutic targets for glioblastoma multiforme, a common and aggressive malignant brain tumor. The study identified three genes strongly correlated with both aging and glioblastoma as potential therapeutic targets.
A study published in Radiology found that AI-based decision support systems can impair radiologist accuracy on mammograms, particularly for less experienced radiologists. Even highly experienced radiologists were adversely impacted by the system's judgments, highlighting the need for safeguards to mitigate automation bias.
Researchers found that using positive trigger words can retrain large language models and result in less biased responses. The team analyzed GPT-2's responses to user prompts about different countries worldwide and found a significant impact on the types of adjectives used to describe citizens.
Researchers identified three novel dual-purpose therapeutic targets using PandaOmics, which could treat both aging and glioblastoma multiforme. The target hypotheses include cyclic nucleotide gated channel subunit alpha 3 (CNGA3), glutamate dehydrogenase 1 (GLUD1) and sirtuin 1 (SIRT1).
A study published in Radiology found that AI can analyze breast mass images from low-cost portable ultrasound machines and accurately identify cancer. The technology showed great promise for improving breast health care in low-resource settings, reducing delays in diagnosis and potentially saving lives.
Researchers from Baidu Research have developed an AI algorithm, LinearDesign, that boosts COVID-19 mRNA vaccine antibody response by 128-fold. The algorithm takes a mere 11 minutes to generate the most stable mRNA sequence encoding Spike protein.
Researchers at the University of Texas at Austin developed a semantic decoder that translates brain activity into text, allowing individuals with speech disabilities to communicate. The system has been trained on extensive hours of podcasts and can decode continuous language, capturing the gist of what is being said or thought.
A study comparing physician and AI chatbot responses found chatbots excelled in both quality and empathy, while physicians were preferred for their nuanced understanding. The findings suggest that integrating chatbots into clinical settings could improve response quality and reduce clinician burnout.
A new feature selection method for text categorization, Max-difference Maximization Criterion (MDMC), is proposed to select discriminant terms. MDMC combines a weight based on class information occupacity with ACC2 to estimate term importance, avoiding overestimation of sparse terms.
A new MIT deep-learning system can analyze the internal structure and properties of materials based solely on their surface conditions. The technique uses vast amounts of simulated data to generate reliable predictions, offering a promising solution for engineers seeking non-invasive insights into material properties.
The Connected Minds program aims to balance emerging tech's benefits and risks for humanity, with a focus on promoting equity and inclusivity. York University has received $82.8 million in federal funding through the Canada First Research Excellence Fund.
Researchers at Sainsbury Wellcome Centre found that instinctual exploratory runs enable mice to learn a map of the world efficiently. The study demonstrates how biological brains can learn faster and more efficiently than AI agents by focusing on salient objects.
A team of IUPUI researchers has developed an AI-powered approach to classify insect species, tackling the challenge of discovering new species. The method uses deep hierarchical Bayesian learning to distinguish between known and unknown species, providing insight into their taxonomy and ecosystem impacts.
A recent study assessed an AI chatbot's ability to answer ophthalmic questions, finding it answered approximately half correctly. The results suggest that while AI has medical advances, the current chatbot is not yet ready for substantial assistance in board certification preparation.
A deep learning AI model has been developed to screen for retinopathy of prematurity (ROP) in infants at risk of blindness. The tool was trained on images of newborns and found to be as effective as senior paediatric ophthalmologists in discriminating normal retinal images from those with ROP that could lead to blindness.
A recent study published in Sleep Medicine warns that AI-collected data may lead to misdiagnosis of childhood sleep disorders. The lack of pediatric data used to train AI models results in biased classification, causing errors in sleep stage identification and potentially severe consequences for young patients.
Researchers at Argonne National Laboratory have developed a self-driving laboratory called Polybot, which automates electronic polymer research and frees scientists' time to work on tasks only humans can accomplish. The tool combines AI and robotics to streamline experimental processes and accelerate discovery.
Researchers developed an AI-based early warning system that combines acoustic technology with artificial intelligence to classify earthquakes and determine potential tsunami risk. The system uses underwater microphones to measure acoustic radiation, which travels faster than tsunami waves and carries information about the tectonic event.
A study by Pohang University of Science & Technology (POSTECH) analyzed water pollution complaints in Alabama and found a significant decrease during the COVID-19 pandemic. The research team used AI methodologies to examine sentiment changes and correlations with climatic extremes.
A study found that high-quality labeling of images boosts perceptions of training data credibility, leading to increased trust in AI systems. However, biases in the data can reduce trust in certain aspects.
Kamaljeet Sanghera has received funding to design a summer program for high school students to learn about AI development and its ethical impact. The pilot project will utilize IBM AI kits to provide hands-on experience and technical skills training.
A massive crowd-sourced study of 327 co-authors at 186 institutions from 14 countries found that ChatGPT scored 47.4% on accounting exam questions, while students averaged 76.7%. Despite struggles with short-answer and higher-order questions, ChatGPT showed promise in improving teaching and learning processes.
A research team from Tokyo University of Agriculture and Technology has developed an image-based AI model to predict the deformation of a splashing drop. The trained encoder-decoder successfully generated image sequences that show the deformation of a drop during impact, demonstrating accurate predictions.
A €10M Horizon Europe grant will support the development of a clinical decision support tool using artificial intelligence to select the best treatment for each individual patient with high blood pressure. The project aims to improve patient care and reduce avoidable consequences such as heart attacks, strokes, and kidney disease.
Researchers have developed a computer-assisted method to automate the assessment of speech severity in ataxia patients, achieving an 80% hit rate. The new methodology leverages artificial intelligence and could simplify procedures for determining ataxia severity, facilitating research and clinical practice.
A study at ECCMID shows AI software can detect TB from chest X-rays with sensitivity and specificity comparable to that of trained radiologists. The technology has the potential to improve diagnosis in low-resource settings where radiologists are scarce.
Researchers developed an AI algorithm that allows electronic devices to express uncertainty when faced with unexpected data, improving cough detection technology. The new approach enables more precise detection with fewer sound samples per second, reducing computing power and addressing privacy concerns.
A new machine learning framework called MILI enables accurate multi-person 3D pose and shape representation from low-resolution images. The approach tackles occlusion issues in multi-person scenes with an occlusion-aware mask prediction network.
A WVU research team has created an OPTIMAL model to help students overcome fears of learning code and enhance critical thinking skills when using ChatGPT, a popular AI chatbot. The model facilitates chatbot-aided scientific data analysis and aims to improve coding skills and prompting abilities.
Newcastle University researchers have developed environmentally-friendly photovoltaic cells that harness ambient light to power IoT devices. The cells achieve an unprecedented power conversion efficiency of 38% and are non-toxic, setting a new standard for sustainable energy sources.