Articles tagged with Data Sets
Dr. Dennis Lal has been appointed as the new executive director of the Center for Innovation in Health Informatics at UT Arlington, succeeding Marion Ball. He will lead initiatives on precision health, clinical AI, and health care-scale informatics.
Researchers from ISTA developed an algorithm that can extract and analyze information from the world’s most extensive biobank with unprecedented accuracy and speed. The method, dubbed gVAMP, enhances the framework's ability to extract complex information from the dataset at hand, providing a detailed overview of the effects on a trait ...
Researchers at UCSF and Wayne State University found that generative AI tools can perform orders of magnitude faster than human teams in analyzing health data. Junior researchers paired with AI generated viable prediction models in minutes, outperforming experienced programmers in hours or days.
A collaborative effort by researchers from the University of Göttingen and other institutions is creating a genomic inventory of European marine annelids. The goal is to accelerate biodiversity research worldwide and counteract the 'silent extinction' of marine species.
A recent NSF grant will support the development of new diagnostics and predictive models for understanding self-competition and weak asymmetry in turbulent flows. The project aims to uncover hidden patterns that current models miss, leading to improved simulations in weather forecasting, climate modeling, and engineering design.
NEXMO Datahub is a mobility data space that enables secure and reliable data exchange between public and private organizations, fostering innovative solutions for smarter and more sustainable mobility. The platform aims to accelerate the digital transformation of the sector through data sharing among key stakeholders.
The State of Open Data report shows open data has become embedded into research practice with FAIR awareness widely recognized. Researchers need systems that reward openness and workflows that make sharing effortless to sustain progress.
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 have launched a new multimodal medical dataset, Observer, capturing anonymized, real-time interactions between patients and clinicians. The dataset links video, audio, transcripts, and electronic health records to study subtleties like body language and environmental factors affecting care.
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.
Researchers analyzed AI methods for detecting pulse rates from facial video recordings and found significant errors at elevated heart rates. The study highlights weaknesses in remote photoplethysmography (rPPG) technique under challenging conditions.
IMDEA Networks has created a secure watermarking tool called FreqyWM, allowing institutions to tag their data with a unique signature and preventing leaks and unauthorized copies. The tool enables the exchange and reuse of information while complying with legal frameworks on security and privacy.
A new report demonstrates how harnessing digital data from mobile phone applications and social media platforms can provide faster, more spatially fine-grained estimates of population movement. This information is crucial for delivering timely humanitarian assistance during crises.
The team created a specialized two-dimensional thin film dielectric designed to replace traditional heat-generating components in integrated circuit chips. This breakthrough aims to reduce the significant energy cost and heat produced by high-performance computing necessary for AI.
A new open-source tool, SCGraph, enables users to calculate the shortest connection between two points worldwide across different transport modes. The system is based on a novel shortest path model that integrates data from road, rail, and maritime routes.
A team of researchers from Binghamton University has created the first-ever high-resolution 3D model of Rano Raraku quarry, revealing over 1,000 moai statues. The model allows users to zoom in and pan across various features, providing a detailed look at the island's quarries and challenging previous theories about its history.
A comprehensive dataset detailing Japanese adults' responses to the pandemic offers unprecedented insights into public attitudes and behaviors. The 30-wave panel survey captures how risk perception, preventive behaviors, and psychological distress evolved over four years.
The Home Health Focus dataset provides insights into Medicare home health use from 2016 to 2019, including demographic data and patient function indicators. The analysis shows a rise in home health stays among beneficiaries while a decrease in active agencies during the same period.
The algorithm identifies the minimum set of locations where field studies would guarantee finding the least expensive route, considering problem structure and uncertainty. This method can be applied to broad classes of structured decision-making problems under uncertainty.
Pusan National University researchers develop a novel prompting technique to improve ChatGPT's accuracy in predicting fashion trends. The study reveals that ChatGPT can capture emerging themes and identify new trends not found in existing data.
The Stowers Institute has appointed its first AI Fellow, Sumner Magruder, to harness the potential of artificial intelligence in biological research. He will collaborate with researchers to design new algorithms and unlock insights from large datasets.
The Global Pathogen Analysis Platform (GPAP) will enable low- and middle-income countries to conduct research and surveillance of infectious diseases independently. The platform aims to prevent disease outbreaks from developing into pandemics by detecting genetic sequences of potential pathogens.
The African Data Drive is an interactive tool that provides accessible, quality-assured spatial data to empower decision-makers to balance development needs with conservation priorities. The platform enables users to assess potential risks to biodiversity and access the most appropriate information on sustainable development.
A new project aims to enhance workforce readiness in molecular bioscience by creating open-access resources and modules tailored to student needs. The Molecular Data Education Hub will host instructional materials and case studies for instructors to implement into their courses.
The Variant Workbench enables researchers to explore genetic data in a single, integrated workspace, linking genomic information with clinical conditions. By reducing data complexity, the tool facilitates scientific discovery and accelerates pace of research.
Researchers at the University of Missouri have developed an AI-powered method to detect hidden hardware trojans in chip designs, offering a 97% accurate solution. The approach leverages large language models to scan for suspicious code and provides explanations for detected threats.
Frontiers' revolutionary AI-powered FAIR² Data Management service is transforming the way scientific data is shared, enabling researchers to fuel progress and earn credit for their work. The service ensures every dataset is preserved, validated, citable, and reusable.
The BIRDBASE dataset covers 78 ecological traits across 11,589 bird species, revealing that 54% are insectivores, with many tropical forest species under pressure. Fruit-eating birds disperse seeds in tropical forests, and fish-eating seabirds face elevated extinction risk.
A new framework for flexible data collection has been developed by Masumi Hisano, allowing for counts to take place in various settings, including cities and daily routines. This approach can help increase sample size and provide valuable insights into bird species assemblage datasets linked to landscape characteristics.
Researchers developed Vesalius to interpret complex data on cancer cell interactions, leading to potential discoveries in treating hard-to-treat cancers. The tool analyzes whole tissue architecture to identify predictive biomarkers and inform treatment options based on individual disease types.
The Intelligent Data Exploring Assistant (IDEA) framework combines large language models with scientific data to analyze complex geoscience data. Researchers can ask IDEA to retrieve data, run analyses, and generate plots using plain-language questions.
Researchers created a large-scale mouse behavior dataset to study complex behaviors like problem-solving and goal-directed actions. The dataset, featuring over 100 hours of footage and detailed human annotations, provides a benchmark for developing algorithms that analyze animal cognition.
A new dataset has been developed to study climate change in the Arctic Ocean. The dataset spans from 1900 to 2100 with high resolution, offering a more accurate understanding of the region's changing climate. It significantly reduces simulation errors and improves representation of key variables.
Researchers found that billing codes may mistakenly identify diseases in up to 45% of cases, highlighting a significant limitation in using administrative data for clinical research. The study examined records of 1.36 million patients and found discrepancies between coded diagnoses and actual disease presence.
Answer ALS is launching a groundbreaking collaboration with Tulane University and the Pennington Biomedical Research Center to harness AI for ALS treatment discovery. The Louisiana AI Drug Development Infrastructure for ALS (LADDIA) will prioritize therapeutic targets using AI-driven insights from the Answer ALS' Neuromine Data Portal.
A conclave of paleontologists, data scientists, and journal editors will meet in Kansas to improve how data is shared among professionals and beyond. The event aims to align paleontological data with FAIR practices, making it easier for researchers to access and reuse.
Researchers from Sapiens Labs created two ongoing data acquisition programs in India and Tanzania to collect large-scale, high-quality neuroimaging data. The programs have collected data from over 7,900 participants with comparable data quality to lab settings and lower costs.
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.
Gene coexpression analysis reveals optimal markers of cell types and states, providing opportunities for developing novel biomarkers and targeted treatment strategies for glioma patients. Dr. Oldham's work tackles the reproducibility crisis in science, emphasizing data metadata standardization.
A research team developed an analytical model to evaluate the performance of grant-free communications schemes in densely populated IoT environments. They found that interference cancellation improved base station throughput but did not resolve the near-far problem, while power control addressed it but led to decreased overall network ...
Researchers have developed an open-access catalog of animal traditions to explore the role of social learning in shaping animal behavior. The Animal Culture Database features vocal communications, mating displays, play, and other social behaviors observed in dozens of species from around the world.
BingoCGN accelerates real-time large-scale graph neural network inference through cross-partition message quantization and a novel training algorithm, achieving up to 65-fold speedup and 107-fold increase in energy efficiency compared to state-of-the-art accelerators.
Researchers found that partial peace agreements play an important role in building trust and strengthening relationships between negotiators. These agreements offer strategic advantages, including consolidating incremental progress, serving as metrics, testing measures, and signaling a larger commitment to the peace process.
A University of Cambridge report argues that menstrual tracking app data is a valuable resource for advertisers but poses significant privacy and safety risks to users. The report calls for better governance of the industry to protect user data and urges public health bodies to launch alternative apps.
Scientists from University of Leicester collaborate with traditional Amazonian communities to monitor biodiversity using artificial intelligence, enabling them to maintain control over their resources and territories. The project aims to reshape conservation approaches in the world's largest tropical rainforest.
Scientists at MIT have identified new potential targets for treating Alzheimer's disease, including a pathway involved in DNA damage repair. The study suggests that a combination of treatments targeting different cellular pathways may be more effective in blocking disease progression.
A new study by University of Cincinnati researcher Edson Chipalo found that children who experienced adverse childhood experiences are at a higher risk of homelessness during their childhood. The study highlights the need for prevention and early support to reduce long-term risks associated with childhood trauma.
A centralized and accessible database aims to integrate molecular simulation data, ensuring findability, accessibility, interoperability, and reusability. This will amplify the impact of these data and avoid duplication.
Researchers developed a new model called React-OT that can predict the transition state of chemical reactions in under a second with high accuracy. The model uses linear interpolation to generate better initial guesses, reducing the number of steps and computation time needed.
A novel method generates binary class labels in highly imbalanced datasets, addressing the challenge of labeling severely imbalanced data. The approach outperformed traditional methods, providing a more efficient way to identify fraud while minimizing false positives.
MIT researchers have found that a computational model of the ventral stream, which processes object recognition, also performs well on spatial tasks such as determining an object's location and orientation. This challenges the dominant perspective that the ventral stream is optimized for object recognition.
Researchers developed a new framework, PAC Privacy, to maintain AI model accuracy and ensure sensitive data remains safe from attackers. The new variant of PAC Privacy estimates anisotropic noise, reducing computational cost and boosting accuracy.
A recent study from UTSA researchers reveals that large language models (LLMs) can pose a serious threat to programmers who use them to help write code. The study found that up to 97% of software developers incorporate generative AI into their workflow, and 30% of code written today is AI-generated.
Researchers found that sleep duration returns to baseline within two days, but changes in sleep timing and structure can take more than a week, with eastward travel causing the most disruption. The study analyzed 1.5 million nights of data from wearables like Oura Ring.
Researchers will use sensors and software to predict AM part lifespan, enabling cost savings and extending part life. The project aims to improve Darwin software to provide detailed insights into manufacturing processes.
The C-Path-led initiative brought together clinical trial sponsors, eCOA technology providers, and regulators to identify and address eCOA implementation issues. Key resources developed during the initiative include guidance on COA data collection and a more open, collaborative environment.
Researchers highlight the underuse of Japanese bird banding data in avian movement research, revealing gaps in our understanding of East Asian migratory birds. The study proposes improving data accessibility and integrating traditional methods with modern tracking technologies to advance conservation efforts.
The new DESI results show that the impact of dark energy may be weakening over time, suggesting a fundamental shift in how we think about dark energy. The collaboration's findings are consistent with other measurements, including supernovae and the light left over from the dawn of the universe.
The Euclid data release unlocks a treasure trove of information for scientists to study the universe's cosmic history and invisible forces. With its exceptional field of view, Euclid captures an area 240 times larger than the Hubble Telescope, delivering outstanding image quality in both visible and infrared light spectrum.
A new study from Aalto University found that global population datasets may underestimate rural populations by as much as 53% to 84%, revealing a systematic and profound extent of the bias. The findings have far-reaching consequences, suggesting that the needs of people living in rural areas have been under-represented in decision-maki...