Articles tagged with Artificial Intelligence
Researchers developed an AI framework that combines dimension reduction techniques with a new clustering algorithm to quickly identify groups of viral genomes at risk. This enables proactive response measures like tailored vaccine development, potentially eliminating emerging variants before they spread.
A study using AI to analyze almost 180,000 food outlets found that restaurants tend to have the healthiest menus, followed by cafes and snack bars. The research reveals a 'double burden' on people living in deprived areas due to high concentrations of unhealthy fast-food outlets.
Current AI dermatology mobile apps can improve access to care, but their efficacy, safety, and transparency are concerns. Regulating these apps is essential to minimize risks and maximize benefits.
A new AI technology has been developed to detect severe cases of retinopathy of prematurity (ROP) with 100% accuracy. The system analyzes retinal images and can identify blood vessel anomalies, enabling early treatment and potentially saving sight for thousands of premature infants globally.
Researchers develop AI-based system to track small metallic objects in Low Earth Orbit, outperforming classical detection methods. The system's high detection rate and low false alarm rates make it suitable for proactive decision-making and intervention strategies.
Researchers at Princeton University have developed a new AI chip that can run powerful AI systems using significantly less energy than existing semiconductors. The chip is designed to be compact and efficient, enabling its deployment in dynamic environments such as laptops, phones, and data centers.
A novel AI-based noise suppression system has been developed to improve the effectiveness of search and rescue drones during natural disasters. The system uses Generative Adversarial Networks (GANs) to accurately learn UAV propeller sound data and eliminate noise, allowing operators to clearly hear and recognize human sounds.
A new study finds that generative AI can accelerate the design of healthcare software, particularly for complex medical problems like diabetes prevention. Researchers at NYU Langone Health used ChatGPT to develop a personalized automatic messaging system in over 40 hours, compared to 200 programmer hours with non-AI enabled efforts.
Researchers analyzed published studies on AI in dermatology, finding significant shortcomings when applied to skin of color. Only 30% of AI programs had data specifically for skin of color, and current programs do worse at identifying skin lesions.
Text-to-image AI tools enhance human artists' output, but may hinder novel visual styles. Artists who adopt AI show increased productivity and favorable feedback, while those relying solely on AI struggle with creative stagnation.
A new study led by Cleveland Clinic researchers suggests that sildenafil may help protect brain cells from Alzheimer's disease. The study found that sildenafil can lower levels of neurotoxic tau proteins and improve brain function in patients with Alzheimer's.
A team of experts at PNNL developed a new tool that sorts and prioritizes cyber threats on the fly, giving grid operators a clear blueprint to identify and address the biggest threats first. The approach uses hybrid attack graphs and optimization to reduce the number of potential attacks from thousands to fewer than 100.
A new cellphone app developed by physician-scientists uses artificial intelligence to accurately diagnose ear infections in young children, reducing unnecessary antibiotic use. The AI tool is more accurate than trained clinicians and offers a simple solution for healthcare providers.
The new skin demonstrates excellent mechanical performance, self-adaptive camouflage capabilities, and long-term stability. It can quickly recognize and match the background by modulating optical signals in response to external stimuli.
Researchers developed an AI technique to expedite the identification of high-performance water electrolyzer electrode materials free of platinum-group elements. These materials can be synthesized using relatively cheap and abundant metallic elements, exhibiting superior electrochemical properties.
A recent study found that GPT-4 scored higher than human participants in three tests designed to measure divergent thinking, an indicator of creative potential. The AI demonstrated higher originality and elaboration in its responses, with improved fluency controlling for human performance.
A Cancer Research UK-funded study uses AI to identify two distinct subtypes of prostate cancer, termed evotypes, which could lead to personalized treatments. The discovery has the potential to improve diagnosis and treatment outcomes, saving thousands of lives in the future.
A KAIST team developed an insect-mimicking semiconductor that mimics the optic nerve of insects to detect motion. The device operates at high efficiency and ultra-high speeds, and has been applied to a neuromorphic computing system for predicting vehicle paths. It achieved 92.9% less energy consumption compared to existing technology.
Researchers developed a model to predict household energy costs with over 74% accuracy by analyzing passive design characteristics from Google Street View images. The model can help identify neighborhoods vulnerable to energy burden and pave the way for smart, sustainable cities.
A breakthrough metamaterial has been developed to enable real-time shape and property control, surpassing existing materials' limitations. The material's adaptable capabilities make it suitable for applications in robotics and other fields requiring flexibility.
A new research review at ECCMID 2024 explores the use of AI in infection control, including ensuring correct mask wear and intelligent cleaning. The key to successful AI use is identifying problems and offloading repetitive tasks to AI systems.
Scientists studied thousands of public photos to track humpback whale populations, finding they're responding to food availability changes affected by climate change. The population declined by 7,000 individuals from 2012 to 2021 due to a massive marine heatwave and reduced prey.
Researchers warn that AI tools used in radiology contribute to greenhouse gas emissions through energy consumption and data storage. To minimize these impacts, experts recommend sharing resources, selecting sustainable hardware, and using data compression techniques.
A recent UConn study assessed the accuracy of ChatGPT's exercise recommendations, revealing that the AI provided only 41% of the expected content in a gold-standard recommendation. The chatbot demonstrated high accuracy for general guidelines but failed to provide key elements such as frequency, intensity, and type of physical activity.
Research suggests AI can identify key risk factors for outbreaks, pinpointing specific
Researchers developed an AI-driven lab called Fast-Cat that uses artificial intelligence to provide in-depth analyses of catalytic reactions. The tool conducts high-temperature gas-liquid reactions and analyzes results to determine how different variables affect the outcome of each experiment.
A new smartphone application using AI and facial-image processing software detects the onset of depression before symptoms appear. MoodCapture captures facial expressions and surroundings, then evaluates them for clinical cues associated with depression.
A Tohoku University team studied deep learning models for diagnosing drowning and found discrepancies between model results and medical experts' observations. The study highlights the need for new training methods that align AI model internals with human expertise.
PandaOmics uses advanced AI algorithms to process vast quantities of diverse data, performing gene and pathway analysis and target predictions. The platform has been extensively validated in multiple therapeutic areas, including oncology, inflammation, and immunology.
A new AI system is being developed to provide real-time feedback and instruction for surgical trainees, addressing the need for constant supervision in laparoscopic surgery. The system uses computer vision model to detect the student's actions and provides immediate assessment and training direction.
Explainable AI methods have been developed to make audio models more interpretable and transparent. Researchers categorize existing audio XAI methods into two groups: general methods and audio-specific methods, offering new possibilities for improving the trustworthiness of AI decision-making in audio tasks.
Researchers identify five grand challenges in biomedical engineering to address social needs, existing gaps, and technological limitations. The Convergence Revolution and Fourth Industrial Revolution are expected to shape the future of medicine, emphasizing interdisciplinary collaborations and next-generation training.
The USC team created a low-cost, customizable learning kit for students to build their own 'robot friend' using the Blossom robot. The three-part module provides hands-on experience and instruction on various AI aspects, including robotics, machine learning, and software engineering.
A new AI-powered system has been shown to detect 40% more polyps during colonoscopies, a crucial step in preventing colorectal cancer. This breakthrough technology uses artificial intelligence to examine every pixel in the image and alert doctors to potential issues, allowing for more accurate diagnoses.
A team of pediatric clinicians developed 45 multilingual videos to educate providers on pediatric care topics, using generative AI and synthetic voice avatars. The videos were recorded in English and translated into Spanish, emphasizing Latin American variations.
A new study published in JAMA Ophthalmology suggests that artificial intelligence can match or exceed the expertise of seasoned ophthalmic specialists in diagnosing and treating patients with glaucoma and retina disorders. The AI system, GPT-4, demonstrated superior performance in response to glaucoma questions and case-management advice.
A new process using artificial intelligence (AI) predicts carbon cycles in agroecosystems, surpassing traditional models in accuracy and speed. This breakthrough enables fair and accurate compensation for farmers, fostering trust in carbon markets and promoting sustainable practices.
Researchers have developed an AI-driven method to detect possible anomalies beneath the surface of wind turbine blades using patented radar technology. The non-destructive approach supports agile data acquisition and analysis, enabling faster detection of manufacturing defects and improved overall quality assurance.
Researchers used AI tool AlphaFold to predict and model over 1,400 protein-protein interactions essential for bacterial survival. The study reveals previously unknown details and offers potential targets for developing new antibiotics.
A Princeton University team developed an AI model that can forecast potential plasma instabilities up to 300 milliseconds in advance, allowing for real-time adjustments to avoid reaction-ending escapes. The model uses past experimental data and demonstrates a promising approach to solving a broad range of plasma instabilities.
A new study by EPFL researchers Antonia Sclocchi and Matthieu Wyart examines the impact of changing batch size and learning rate on stochastic gradient descent. They identify three regimes that affect AI learning differently, from exploratory to efficient approaches.
A study published in PNAS Nexus found that AI-generated propaganda was almost as effective as real propaganda in persuading US adults. The research used a large language model to generate new articles based on existing propaganda, with 43.5% of respondents agreeing with the claims after reading the AI-written articles.
Researchers at Simon Fraser University have developed an AI approach to intrinsic decomposition, separating images into lighting effects and true colours of objects. This innovation enables a range of applications, including image compositing and augmented reality, making it accessible to content creators and post-production artists.
A recent study found that parents and clinicians are in favor of a mobile app to help manage child cancer pain at home. The app aims to ease the burden on caregivers and provide personalized pain management support. Recommendations for the app include improved accessibility, language options, and gamification features to involve children.
The NSF director highlights the benefits of AI in scientific research, from accelerating discovery to automating routine tasks. He emphasizes the need for safe and accessible AI, calling for a diverse AI ecosystem that incorporates broad perspectives and problem-solving approaches.
The Heidelberg Laureate Forum Foundation offers limited international journalist travel grants to report on the event. Journalists can apply until April 28, 2024, and will cover travel and visa costs, as well as room and board during their stay in Heidelberg.
Researchers at North Carolina State University are developing a suite of performance metrics to standardize the evaluation of self-driving labs in chemistry and materials science. These metrics aim to compare different lab technologies and identify areas for improvement, ultimately advancing the field and accelerating discovery.
A KAUST research team has developed a machine-learning approach that balances privacy preservation and model performance using ensemble privacy-preserving algorithms. The approach, called PPML-Omics, achieves better model performance while keeping the same level of privacy protection compared to previous methods.
Researchers from Argonne National Laboratory and the University of Illinois Urbana-Champaign used generative AI to quickly assemble over 120,000 new MOF candidates for carbon capture. The approach combines AI with high-throughput screening, molecular dynamics simulations and theory-based design to identify optimal materials.
A new AI tool, DeepGO-SE, successfully predicts the molecular functions of unknown proteins with high accuracy. This breakthrough enables researchers to analyze uncharacterized proteins, facilitating tasks such as drug discovery, metabolic pathway analysis, and disease associations.
Researchers analyzed over 1,000 studies to identify design principles for creating empathic conversational agents. The study reveals the importance of emotional intelligence and adaptive feedback in improving learning outcomes.
Researchers used data from 9,300 miles of Greek roads to develop a machine-learning model predicting crash sites. The model identified key features such as abrupt speed limit changes and incomplete lane markings as predictors of crashes. The study's findings have implications for improving road safety globally.
A study found that customers are more willing to provide written compliments and complaints using AI-powered tablets rather than leaving videos. The researchers suggest that methods requiring 'low self-disclosure' would work better for customer feedback.
Researchers at UC Santa Cruz find that popular link prediction metrics are flawed and do not accurately measure algorithm performance. They recommend using a new metric, VCMPR, to benchmark link prediction tasks and highlight the importance of accurate metrics in machine learning decision-making.
A new depth from focus/defocus approach, DDFS, combines model-based and learning-based strategies to achieve notable improvements in performance and applicability. The proposed method outperformed state-of-the-art methods in various metrics for several image datasets.
A new paper argues that LLMs can interpret and analyze neuroscientific data, unlocking new insights and potential treatments. Lead author Danilo Bzdok suggests that scientists may not always fully understand the mechanism behind biological processes discovered by LLMs.
A new tumor spatial mapping tool will help clinicians assess the aggressiveness of cancer and personalize treatment. The tool maps the functional state of oncoproteins onto tumour images, allowing for more accurate diagnosis and informed treatment decisions.
Researchers developed sensors using aerogels to detect formaldehyde, a common indoor air pollutant, with real-time detection capabilities. The sensors require minimal power and can distinguish between different gases.
Researchers developed an AI model to detect low blood sugar levels in diabetics while driving, improving safety and preventing accidents. The model uses driving behavior and head/gaze motion data, showing promise for future self-driving cars.
A clinical trial found that patients who received care recommendations from an AI-based system had fewer recurrent strokes, heart attacks, or vascular death within three months. The study suggests that this technology can improve patient outcomes and aid neurologists in making informed decisions.