Articles tagged with Data Sets
Researchers at KAUST develop a novel multivariate skew-elliptical link model to address the challenges of highly imbalanced health data. The new model provides a better fit to COVID-19 datasets and offers flexibility over existing models.
A new study by MIT researchers shows that mobile phones can collect useful structural integrity data while crossing bridges. The study found that information about bridge vibrations can be extracted from smartphone-collected accelerometer data, and that this method could add years to a road bridge's lifespan. By leveraging crowdsourced...
Researchers at University of Jyväskylä used machine learning to predict ACL injuries in elite athletes but found a low overall accuracy rate. The study analyzed the largest data set ever collected and provided valuable insights into the challenges of predicting injuries in individual athletes.
Researchers used machine learning to track turbulent structures in fusion reactors, gaining detailed information on their behavior and heat flows. The approach enables more accurate engineering requirements for reactor walls and could lead to improved energy efficiency.
The Global Jukebox, an online tool for exploring music and performing arts from around the world, has made its dataset and data available to the public. The database includes 5,776 recordings representing 1,026 societies, with detailed musical style categorization data and additional features such as breath management and instrumentation.
The US Department of Energy's Oak Ridge National Laboratory has developed a massive geographic dataset, USA Structures, using deep learning to forecast potential damage and accelerate emergency response. The dataset provides critical information on building outlines and attributes, enabling FEMA to prioritize response efforts.
A joint study by TAU and Hebrew University accurately dated 21 destruction layers at 17 archaeological sites in Israel, using geomagnetic field reconstruction. The new data verify Biblical accounts of Egyptian, Aramean, Assyrian, and Babylonian military campaigns against the Kingdoms of Israel and Judah.
Researchers analyzed COVID-19 conspiracy theories on Twitter, finding that some peaked at the beginning of the pandemic while others remained persistent throughout. The study suggests that risk perceptions and lack of information from governments and experts contributed to the persistence of these theories.
A new dataset provides an unprecedented insight into the Arctic Ocean's biological life, revealing a year's worth of microbial communities and their responses to climate change. The EcoOmics dataset aims to guide conservation efforts and provide evidence for novel biology that may influence our understanding of evolution on Earth.
A study found that Italian regions with high levels of environmental pollution have higher cancer mortality rates, even after controlling for lifestyle factors. The analysis identified specific sources of pollution associated with certain types of cancer, highlighting the need for environmental reduction and prevention to combat cancer.
A University of Groningen team created two machine learning models to predict app removal risks, achieving accuracy rates of up to 79.2%. The models can help developers avoid bans and users protect their data.
The Keck School of Medicine's Stevens INI has received a nearly $2 million grant to upgrade its storage system, increasing its capacity to handle vast amounts of brain imaging data. This will enable the lab to maximize scientific productivity and fulfill its promise to collaborate with researchers globally.
A new study by Cornell University researchers found that nearly all market research panel participants are at risk of being de-anonymized due to the presence of quasi-identifiers. The reidentification risk can be up to 94% when considering multiple observations per panelist, highlighting the need for improved data privacy measures.
Researchers aim to create a unified database network for battery data, facilitating AI analysis and predictions. The Battery Data Genome will collect data across the entire battery lifecycle, from discovery to deployment, with uniform standards for metadata.
Researchers developed a tool that encodes patient data as DNA sequences to link health databases accurately. The platform uses BLAST and machine learning algorithms to integrate data from multiple administrative databases, overcoming typographical errors and inconsistencies.
Researchers found that 12% of cancer survivors lived in poverty, experiencing negative effects on physical and mental health. Financial burden of cancer care persists years after diagnosis, leading to poor health outcomes and increased mortality.
Researchers found that a common autism screening test consistently excludes more women than men from research studies, creating a 'leaky pipeline' for diagnosis and treatment. This bias is attributed to the test's origins in male-dominated samples, which may not accurately capture female phenotypes.
Researchers from Children's Hospital of Philadelphia used advanced mapping techniques to identify causal genes and target pairings in the pancreas linked to type 2 diabetes. The study revealed alpha and acinar cells play a greater role in disease development than previously thought.
Researchers at King Abdullah University of Science & Technology (KAUST) have developed a more robust and realistic general method for dealing with wind-driven phenomena in geostatistical modeling, which promises to greatly improve the accuracy of pollutant dispersion prediction.
A new study from North Carolina State University shows that soil temperature can be used to predict the spread of the corn earworm, an important pest affecting various crop species. The research reveals three geographic zones where the pest can overwinter, and models suggest that these zones will shift northward due to climate change.
Rice University's ROBE Array algorithm slashes the size of DLRM memory structures, allowing training on 100 megabytes of memory and a single GPU. The method matches state-of-the-art DLRM training methods with improved inference efficiency.
Thirty-eight Chinese cities have reduced their CO2 emissions for at least five years, while 21 cities have cut emissions due to economic decline or population loss. The study recommends individualized emission targets considering cities' resources and development goals.
Mandated PDMP use in US states reduced opioid prescriptions by 6.1% but led to a 50.1% increase in heroin-related deaths, according to researchers from the University of Texas at Dallas.
Researchers developed a digital health system approach to enhance clinical decision-making for low-back pain sufferers. The system combines self-reported pain measures with precise motion-sensing data, revealing functional improvements only after six months of surgery.
A new Harvard-led study reveals that rising global temperatures caused the explosive evolution of early reptiles, challenging previous explanations. The research suggests climate change triggered morphological changes in reptile groups, including those that gave rise to crocodiles and dinosaurs.
Researchers assembled a large biologging dataset to understand how sharks, rays, and skates use the ocean depths. They found that many species migrate vertically in response to food resources, with some diving to extreme depths.
A new study found that 'gaps' within DNA protein and sequence alignments can provide valuable information about nucleotide and amino acid substitutions. The finding is particularly relevant for studying distantly related species.
A new study from North Carolina State University reveals no-till farming boosts agricultural land values in the Midwest, with a 1% increase translating to a $7.86 per acre gain. This finding supports the economic and environmental benefits of adopting soil conservation practices like no-till farming.
Researchers at Cedars-Sinai created complex computer models of individual brain cells using artificial intelligence. These models capture the electrical signals that neurons fire to communicate with each other, allowing researchers to replicate brain activity at the single-cell level.
Researchers aim to uncover information on blotchy bass syndrome's prevalence, distribution, and potential risks through data collected by citizens. The study will help determine which bass species are susceptible and which seem immune.
The new database offers improved estimations of Potential Evapotranspiration and Aridity Index for the entire world at a high spatial resolution. This allows for a finer description of water needs in different regions, enabling better resource management and land-use planning.
Researchers have centralized over 300 key figures in the Human Impacts Database, providing information on global plastic production, standing livestock population, and sea level rise. The database aims to promote collective quantitative literacy of the Anthropocene.
The new AI system uses associative learning to detect similarities in datasets, reducing processing time and computational cost. By leveraging optical parallel processing and light signals, the system can identify patterns and associations more efficiently than conventional machine learning algorithms.
A new study by researchers at the University of Oxford found that ageing female wild red deer on the Isle of Rum in Scotland tend to adopt a life of solitude as they grow older. They interact with fewer other individuals within their home ranges and shift to less populated areas of their habitat.
A comprehensive global dataset of lakes and reservoirs has been published, offering new information on land and fresh water use. The research provides a better understanding of the impact of changing climate and human actions on global freshwater resources.
A new study uses machine learning models to predict cancer patients' responses to immunotherapy based on their gut microbiome features. The research identifies common gut bacterial taxa associated with responders versus non-responders, providing a potential tool for distinguishing and predicting immunotherapy responders.
Provincial health ministries hold COVID-19 vaccination data but have been reluctant to share it with researchers. Establishing partnerships between provinces and the Health Data Research Network would enable timely data transfer and support research into vaccine effectiveness.
A comprehensive dataset of over 1000 shark-human interactions in Australia helps scientists identify patterns linking environmental, biological, or social factors to shark bites. The database can inform decision-making on mitigation measures, such as wetsuit design and shark deterrent devices.
Researchers developed a novel convolutional neural network for facial expression recognition, outperforming conventional models while being computationally less expensive. The new model achieved an accuracy of 72.4% using only 58,000 parameters.
A University of Washington study found that Pacific salmon in larger groups have lower predation risk, but may trade safety for food. The researchers analyzed historical data on fish catches and predator wounds to estimate group size and predation risk, revealing the benefits and costs of schooling in marine fish.
A newly expanded data set of brain scans from stroke patients called ATLAS now includes 1,271 MRI images with manually segmented lesions, facilitating large-scale stroke recovery research. Researchers hope to develop algorithms to automate lesion segmentation, enabling clinicians to predict patient responses to therapies.
A new study shows that community science activities can produce high-quality taxonomic data sets, empowering community scientists and supporting biodiversity discovery. Thousands of microscopic liverwort leaves were measured by community scientists over two years, with surprising accuracy.
Researchers have developed an app to help doctors identify patients with chronic lymphocytic leukemia (CLL) at risk of developing infections, allowing for earlier treatment. The app uses blood test results and genetic data to predict patient risk, improving treatment outcomes and reducing pressure on the healthcare system.
A new study reveals that population declines have been greatest among species that migrate to areas with more human infrastructure, habitat degradation, and climate change. The research identified 16 human-induced threats to migratory birds, including infrastructure associated with bird disturbance and collisions.
The American College of Cardiology and the American Heart Association have released a comprehensive data standard to standardize definitions for COVID-19-related cardiovascular conditions. This framework will help pool or compare data from various sources to assess its applicability to clinical practice and research endeavors.
A new report highlights the nation's race and ethnicity data shortcomings, recommending federal leadership on standardizing demographic data collection and reporting across critical issue areas. The report aims to help policymakers craft solutions that take into account where resources should be concentrated to address racial disparities.
A massive dataset from Binghamton University tracks public health government responses to COVID-19 at all levels of government worldwide. The dataset provides insights into the effectiveness of different types of government in responding to global crises.
Feminicide, a worldwide problem resulting in 87,000 intentional killings of women in 2017, has incomplete data due to undercounting and narrow legislation. Researchers using counterdata aim to enact alternative epistemological approaches centering care, memory, and justice.
A study by WVU researcher Ednilson Bernardes found that supplier pool pressure contributed to the oversupply of prescription opioids like oxycodone and hydrocodone. The researchers analyzed transactions from 2006-2012, revealing that over 90% of supply came from just three generics manufacturers.
The INCLUDE Data Hub provides centralized access to large-scale research resources, including biospecimen libraries and clinical datasets, for the study of Down syndrome. With over 8,000 study participants and 30,000 biospecimens, researchers can accelerate discoveries that benefit people with Down syndrome.
A recent study published in Big Data & Society found that Democrats and Republicans in the US surveyed agree on the mathematical features of COVID-19 graphs, such as line slopes, but differ in their subjective interpretations. The researchers suggest that political affiliations may moderate how people interpret data, highlighting the i...
The study collected sensor data and conducted surveys to understand the conditions people experience as they move about their daily life. The dataset provided a granular picture of temperature exposure, revealing that participants were well-situated to maintain low temperatures, but still faced dangerously hot environments.
Researchers developed a methodological framework to ensure web data validity in marketing studies. The study provides recommendations for addressing challenges in collecting and using web data via web scraping and APIs.
Researchers at MIT found that explanation methods used to aid human decision-makers in high-stakes situations often have lower accuracy for minoritized subgroups. The fidelity of these explanations varies dramatically between subgroups, with the quality often significantly lower for women and Black people.
A WHO-supported series has collected 13,700 new database records on mosquito-borne diseases, providing valuable resource for studying and containing infectious diseases. The data can be used to train machine-learning models for vector detection and classification, improving global human health.
A significant overestimation of arterial oxygen saturation by pulse oximetry was found in Asian, Black and Hispanic patients compared to non-Hispanic white patients. This discrepancy led to unrecognized and delayed recognition of COVID-19 treatment eligibility among these groups.
A Kyoto University study shows that even though biodiversity increases with more interactions, mean interaction strength decreases. The interaction capacity hypothesis proposes that this weakening of interspecific interactions may be due to increased community diversity.
A new tool called DeepSqueak uses deep learning to identify marine mammal calls with high accuracy, even in noisy environments. The tool was originally developed for rodent ultrasound signals but has been adapted to detect sounds at other frequencies, including humpback whales and delphinids.
A new analysis found that citizen science data from apps like eBird can be a valuable resource for researchers and managers, offering insights into wild bird populations. By comparing publicly-produced data with officially tracked numbers, researchers have identified patterns and potential areas for improvement.
Scientists have developed a machine learning algorithm that can accurately predict the lifetimes of different battery chemistries using as little as a single cycle of experimental data. The technique could reduce costs and accelerate the development of new battery materials, enabling researchers to quickly evaluate and test multiple ma...