Articles tagged with Data Visualization
The University of Ottawa Heart Institute, McGill University, and the University of Ottawa have launched ARCHIMEDES, a national health data platform providing Canadian researchers with secure access to diverse health data. The platform enables collaboration, supports advanced analyses, including AI algorithms, and prioritizes public trust.
This study assesses the educational impact of introducing interest-matched examples in data science education, showing a positive effect on students' motivation and understanding. The findings suggest that instructional approaches grounded in intrinsic motivation theory can improve data science education quality.
A study by Bielefeld University used anonymized WhatsApp metadata to show that personalized feedback can help people understand their communication habits. Many participants adjusted their views on response speed and chat participation after seeing data-based visualizations.
Researchers found science fiction and genre elements were popular among readers, with top authors including Ursula K. Le Guin and Octavia E. Butler. The analysis also revealed trends driven by news events and the selection of canonical authors for the Seattle Reads program.
The Global Centre for Asian Women’s Health has partnered with NUS Medicine to host the Women’s Health Impact Tracking (WHIT) platform, which measures progress on closing the women’s health gap across a set of conditions and countries. The platform provides clear, comparative insights to support decision-making and inform policies.
Two US-based teams, FigureTwo and Syntheos, have won Digital Science's 2025 Catalyst Grant for their innovative data visualization projects. FigureTwo transforms static figures into interactive visuals, while Syntheos maps ideas across research communities to show impact.
A new study maps three decades of income inequality data globally, revealing worsening trends for half the world's population but 'bright spots' in regions with effective policies. Regional efforts such as investments in public health and education in India and cash transfer programs in Brazil show promise in reducing inequality.
University of Missouri researchers are combining in-home sensor technology with artificial intelligence to monitor daily changes in ALS patients' health. The system uses machine learning to estimate a patient's score on the ALS Functional Rating Scale Revised, predicting potential problems before they occur.
Researchers developed DeMemSeg, an AI-driven pipeline that accurately segments overlapping membrane structures with accuracy comparable to expert manual analysis. The approach enables large-scale, objective, and quantitative analysis of morphological data, providing a foundational technology for advancing disease mechanisms.
A study by University of Arizona researchers found that selecting the right data for flood insurance can significantly improve accuracy, speed, and predictability. The type of data used affects not only payout timing but also confidence in anticipating future payouts, influencing program costs.
Researchers at Linköping University used magnetic cameras to examine blood flow in an artificial heart in real-time, revealing a pulsing pattern similar to that of a healthy heart. The study aims to design the heart to minimize complications such as blood clots and red blood cells breakdown.
The study reveals data visualization primarily facilitates decision-making at the organizational and community levels, particularly for semi-structured problems. Recent trends indicate increasing support for broader types of decision-making, including individual-level and unstructured problems.
The grant aims to support novel applications of data visualization technology that benefit various stakeholders in the research ecosystem. Successful applicants will receive up to £25,000 for their innovative tech ideas.
The joint policy brief from four EU projects aims to guide successful implementation of the Green Deal Data Space. It recommends standardised data exchange technologies, inclusive governance frameworks, and metadata management to unlock Europe's full potential in environmental data.
The new GseaVis package offers highly customizable visualizations, including enrichment plots, ranked gene heatmaps, and circular layouts, addressing the limitations of existing tools. It integrates seamlessly with established R libraries and workflows, making it accessible to researchers at various skill levels.
The new compute roadmap aims to improve lives and livelihoods with advanced computing power. It includes investments in AI research, healthcare diagnostics, and renewable energy.
Researchers at Notre Dame's School of Architecture and the Lucy Family Institute for Data & Society developed EcoSphere, an AI-powered platform that visualizes embodied carbon emissions. The tool helps city planners identify strategies to reduce carbon emissions through renovation and extended building life.
A new wearable device measures breast milk intake in real-time, providing clinical-grade monitoring of breastfed babies. The device eliminates uncertainty around milk consumption, reducing parental anxiety and improving clinical management for vulnerable babies in the NICU.
A new review advocates for building confidence in AI applications by implementing robust data governance frameworks, enhancing transparency, and involving stakeholders. The authors emphasize the importance of addressing ethical implications and ensuring equitable access to AI-driven innovations in clinical oncology.
A new study from the University of Missouri highlights how 'smoothed' graphs can help doctors better manage patients with hypertension. The findings suggest that these graphs can reduce errors in assessing blood pressure control, potentially alleviating pressure on the healthcare system.
Researchers at the University of California San Diego have made a groundbreaking discovery about how our brains learn new information. Using sophisticated imaging techniques, they found that individual neurons follow multiple rules during learning, rather than one set of uniform rules as previously thought. This new understanding has s...
Researchers at Saarland University are developing leaner, customized AI models and techniques like knowledge distillation to reduce energy consumption. These smaller models enable small and medium-sized businesses to access powerful AI technology without a large technical infrastructure.
Researchers at the University of Konstanz have developed tactile learning materials that allow students to explore mathematical concepts and scientific data using touch. The project, Geo3DTouch, aims to create inclusive access to education for people with sight impairments by providing 3D printed prototypes and detailed instructions.
A new laparoscopic imaging technique uses stereo depth estimation and speckle-illumination SFDI to accurately map the optical properties of biological tissue. The device provides detailed optical property maps, enabling surgeons to identify critical tumor margins and improve clinical outcomes.
Researchers have developed a Minecraft plugin, CraftCells, that allows users to visualize and explore biological cells in three dimensions. The tool enables players to navigate through cell membranes, organelles, and cytoplasm, providing insights into cellular structure and organization.
A new computational tool, PsiPartition, simplifies genetic data analysis for evolutionary biology, allowing researchers to efficiently study species relationships. The novel method improves both computational efficiency and accuracy of phylogenetic trees.
The Association for Computing Machinery (ACM) has named 55 Fellows for their transformative contributions to computing science and technology. The inductees represent a diverse range of fields, including cybersecurity, artificial intelligence, human-computer interaction, machine learning, and programming languages.
The University of Illinois Urbana-Champaign has received USGIF accreditation for its online graduate certificate and master's degree in CyberGIS and Geospatial Data Science. The partnership will train students to address large-scale problems using geospatial sciences, mathematical and statistical sciences, and cyberinfrastructure.
Researchers developed a cutting-edge method leveraging Graph Neural Networks (GNNs) to predict mesozooplankton community dynamics and visualize their interactions. The study achieved remarkable improvements in forecasting accuracy by integrating inter-series relationships and temporal dependencies among input-variables.
A research team at Pohang University of Science & Technology developed a technology that visualizes the deformation of 'serpentine' structures in real-time through color changes. This innovation eliminates the need for complex nanofabrication processes, providing actionable design guidelines for optimizing these structures.
A WVU researcher creates an augmented reality training program to enhance miners' awareness of blind spots and ability to identify hazards. The training technology uses visualizations to project blind spots directly onto the trainee operator's surroundings, reducing fatalities and injuries in the mining industry.
Researchers developed a new method, k* distribution method, to visualize and assess how well deep neural networks categorize related items together. The model reveals clustered, fractured or overlapping arrangements of data points, indicating accuracy and reliability issues.
A study by Politecnico di Milano reveals districts most at risk of cardiovascular emergencies during heat waves in Milan. The research found that 23% of the city's population in 18 vulnerable districts face a 22% increased risk, while 20 low-vulnerability districts show no significant increase.
Scientists visualized the ultrafast dynamics of molecule dissociation using a new analytical method at BESSY II. The results show that lighter atom groups are ejected first, followed by heavier fragments. This process unfolds rapidly, similar to a 'molecular catapult' effect.
Researchers introduce a new tool called 'persistence images' that uncovers hidden biases in medical imaging data, advancing fairness in healthcare AI. The technology helps detect bias, filter out noise, and improve overall accuracy, leading to more reliable diagnoses and better patient outcomes.
A new AI tool generates realistic satellite images of future flooding, which can help communities visualize and prepare for approaching storms. The method combines a generative artificial intelligence model with a physics-based flood model, producing more accurate and realistic images than an AI-only approach.
Researchers introduce persistence barcodes, a tool that reduces diagnostic bias and uncovers subtle details in medical images. The method preserves key structural details, enabling clearer insights into the data.
Devin Harris and his team have developed an augmented reality app, STRUCT-AR, that allows students to 'stress test' virtual bridges, beams, frames, and trusses. The app, which is set to be tested this spring, aims to improve students' understanding of structural behavior by providing a more interactive and immersive learning experience.
Researchers developed an algorithm to analyze high-resolution spatial data from Seq-Scope and other technologies, called FICTURE. This enables scientists to see how and where a gene is expressed at microscopic resolution, improving our understanding of gene expression.
Researchers developed a novel neural network model to reconstruct 3D digital images of relief-type cultural heritage objects from old photos. The model improves the accuracy of depth estimation and soft-edge detection, enhancing the preservation of cultural heritage.
Researchers develop a novel edge-highlighting visualization technique to improve the clarity of complex 3D structures, revealing sharp edges and intricate details. The technique, tested on real 3D point cloud data, offers interactive rendering speeds and enhances depth perception.
Researchers have developed Rastermap, a visualization tool that enables scientists to uncover activity patterns in thousands of neurons. The tool sorts neuronal activity into clusters based on similarity and maps them onto a graphical representation, allowing for the identification of patterns that can be further tested in the lab.
Parachute fibers' behavior under stress was studied using micro-CT scans, revealing they are not isotropic and respond differently to increasing loads. The findings inform processes like parachute assembly and improve models for screening parachute materials, making industries more cost-effective and time-efficient.
The European Southern Observatory's VISTA telescope has created the largest infrared map of the Milky Way, comprising over 200,000 images and covering an area equivalent to 8600 full moons. The dataset contains about 10 times more objects than a previous map released in 2012, including newborn stars, globular clusters, and brown dwarfs.
Notre Dame researchers have created a new tool to analyze embodied carbon in over 1 million buildings in Chicago, providing policymakers with actionable data to inform urban development decisions. The study found that extending the lifespan of buildings and reducing their size can decrease carbon emissions by two-thirds.
A new four-year, $459,000 grant will develop software and hardware tools to increase accessibility in STEM fields for persons with disabilities. The project aims to enhance data technologies for blind and low-vision users, making it easier for them to participate in STEM research and education.
University of California San Diego researchers used cryo-electron microscopy to capture the first 3-D images of a key muscle receptor, shedding light on why newborn humans develop slowly while cows mature quickly. The study's findings may help develop future treatments for muscular disorders.
Researchers at HIRI and THWS develop a desktop application to visualize scRNA-seq data, enabling interactive 3D exploration of gene expression in single cells. The tool allows users to focus on specific cell populations or genes of interest, facilitating better understanding of bacterial defenses against antibiotics.
The study creates two 3D maps at once by combining near-infrared absorption imaging with image processing, providing insights into optimizing micro-heating and cooling devices. The technique promises to deliver new knowledge on convective plume formation at the microscale.
The Indiana Sickle Cell Dashboard presents interactive visualizations of the disease's prevalence and burden across an entire state, offering a comprehensive picture of those living with sickle cell. The dashboard provides rates per 100,000 population, allowing for comparisons between states or areas around the world.
Researchers from MIT and the MIT-IBM Watson AI Lab devised a navigation method that converts visual representations into pieces of language, which are then fed into one large language model. The approach utilizes purely language-based representations, generating synthetic training data to overcome challenges in visual data availability.
Texas A&M University researchers have developed a 3D visualization technology to identify potential outcomes of hurricane flooding before it occurs. This allows for improved safety and reduced damage costs. The technology can also model specific buildings, accounting for basements, back entrances, and windows.
Researchers from the University of Tokyo have developed a framework to analyze and visualize population mobility data, which could help in allocating resources and personnel effectively. The study used GPS data from displaced individuals in Russia's invasion of Ukraine, revealing patterns of migration that vary by socioeconomic status.
Researchers developed an algorithm to stratify people with type 2 diabetes using routine data, revealing metabolic diversity and insulin sensitivity variability. The study's findings have the potential to change the way we understand and treat type 2 diabetes.
A new auxiliary CHD diagnostic system has been developed to identify TTE cardiac views, integrate information from various views and modalities, and predict the probability of a subject being normal or having a heart defect. The system uses a hierarchical network structure and has been shown to accurately detect children with CHD.
The event standardised and improved accessibility of biodiversity data, enabling informed policy-making and conservation efforts. Ten teams showcased their solutions to a jury of experts, with winning projects illustrating the versatility of data cubes in facilitating biodiversity conservation.
The St. Jude survivorship portal provides a rich dataset for researchers to study childhood cancer survivors, including genomic and clinical information. The portal facilitates breakthroughs in pediatric cancer survivorship research through dynamic visualization and customizable charts.
Concordia researchers use network analysis to study cognitive decline, identifying key variables that predict subtle changes in brain function. Executive function and processing speed are found to be strongly influential, with age affecting cognition differently for those with mild cognitive impairment or Alzheimer's disease.
Researchers at University of Missouri are developing software that allows drones to fly independently, perceiving and interacting with their environment while achieving specific goals. This technology has the potential to assist in mapping and monitoring applications, such as 3D or 4D advanced imagery for disaster response.
A landmark study stratifies people with type 2 diabetes using routine variables to visualize metabolic diversity. The algorithm identifies different subtypes of the disease, which can help in targeted prevention and treatment.