Articles tagged with Data Availability
A new study published in the Obesity journal surveyed nearly 2,500 WeightWatchers members who lost an average of almost 58 pounds and kept it off for over 3.5 years. The study found that individuals who successfully maintained weight loss resumed efforts responsively after showing limited gains and used coping skills to get back on track.
Research finds public perception of data use is shaped by social inequalities and concerns about potential harm or corporate profit. Experts highlight need for public sector review of data-driven systems to address these issues.
A new study published in GigaScience has made available an enormous amount of behavioral data from an animal model of obsessive-compulsive disorder (OCD), comprising over 2 years of continuous recording. The data set, which is the culmination of a 15-year study, provides insights into the mechanisms of OCD and potential treatments.
Vivli's generalist repository is the largest clinical trial repository in the world, providing managed access to over 6,600 trials. The platform has contributed to over 100 publications and features a COVID-19 portal with quick data addition capabilities.
A new platform has been created using 214,000 microbiome samples to track antibiotic-resistant bacteria globally. The data can be used to tailor guidelines on combating resistance in different regions.
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.
Mathematical models suggest that only 1 in 5 COVID-19 cases were counted worldwide, resulting in an estimated 600 million to 2.4 billion actual cases globally. The wide range of estimated cases highlights the problems with accuracy of reported numbers due to data tampering, inconsistent reporting, and lack of uniformity.
Researchers reviewed mobile sensing designs, outcomes, and limitations to better understand its capacity for remote detection, longitudinal tracking, and exposure tracing. Despite technical and societal challenges, advances in data analytics and machine learning may improve data quality and scalability.
A new study found that disclosure of advertising spending significantly lowers investor and analyst uncertainty, enhancing firms' valuation. The study analyzed 2,285 publicly listed firms over 25 years and found a moderate negative effect on idiosyncratic risk.
Researchers developed a mobile phone app using AI to accurately detect COVID-19 infection in people's voices, outperforming lateral flow tests. The app achieved an accuracy of 89% and can be used for remote testing, enabling rapid screening of populations.
A new study led by York University finds that lower-to-middle-income countries struggle with high unemployment rates after COVID-19 lockdowns and economic restrictions. In contrast, higher-income countries such as Canada have better managed their unemployment rates.
Public health researchers developed a global vaccine risk index (VRI) to predict vaccine coverage lapses worldwide. The VRI considers factors like measles incidence, vaccine confidence, climate change, education, and income, revealing countries at high risk of disease outbreaks.
Researchers found a lower concussion rate in Florida, where headgear was mandated, compared to states without. The rate was 0.39 concussions/1000 athlete exposures with mandatory headgear, vs 0.44 without. This suggests that headgear may be worth considering for high schools and other levels of play.
Researchers found that providing default alternatives and using ordering and partitioning together can improve consumer choice. This study aims to provide a more efficient way for consumers to make better decisions about healthcare products, ultimately improving health outcomes and the efficiency of the healthcare system.
A proof-of-concept study developed three machine learning models to predict posttreatment recurrence in early-stage hepatocellular carcinoma patients. The models achieved high accuracy using imaging data alone, while combining clinical data did not significantly improve performance.
Researchers used natural language processing and machine learning to analyze nearly 35,500 death records, identifying the most common substances involved in overdose deaths. The system reduced data processing time by months, allowing for more rapid public health responses and interventions.
A multi-national study found that over half of clinical trials leading to FDA-approved anticancer medicines are not available for independent scrutiny. The lack of transparency hinders the use of data for further research into the safety and efficacy of medicines.
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 new platform called MoveApps enables scientists and wildlife managers to explore animal movement data with little more than a device and a browser. The system uses open-source code and allows users to create complex analyses with simple clicks.
Researchers developed three new bike count models combining traditional location-based data with crowdsourced GPS data, showing improved accuracy in predicting bicycle volumes. The models demonstrated the value of integrating different data sources to enhance transportation planning.
The WHO advises against the use of colchicine and fluvoxamine for treating non-severe COVID-19, citing insufficient evidence and potential harms. No recommendation is made for these drugs in patients with severe or critical illness.
A new study from NYU Tandon School of Engineering uses a spatio-temporal model to predict firearm prevalence on a state-by-state level. The researchers found that combining data from background checks per capita and suicides committed with a firearm in a given state can provide precise information regarding firearm ownership.
A study found that citizen science volunteers are predominantly white and educated, with a high percentage of STEM professionals, highlighting the need for more diverse recruitment strategies. Many volunteers join multiple projects, indicating a willingness to participate in scientific research.
The integrated tool allows tracking of clinical trial enrollment and cost effectiveness, enabling study teams to ensure trials are the best fit for the enterprise. It also enables standardization of data collection and reporting, giving the institution a competitive edge.
A UK-based research project aims to investigate the specific threats posed to female garment workers in supply chains globally. The four-year study will examine garment manufacturing in the midlands, UK, and in Cambodia, Ethiopia, and Jordan.
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.
A collaborative initiative aims to establish common protocols for assessing and comparing diffuse optics systems used in medical diagnosis. The study presents the results of a multi-laboratory comparison of 12 institutions and 28 systems, proposing simple numeric values for easy comparison across instruments.
A recent study published in Angewandte Chemie found that AI models struggle to predict reaction yields due to biased data, mainly caused by a lack of reported failed experiments. The researchers attribute this failure to three possible causes: experimental error, personal bias, and underreporting of negative results.
The Hubble Space Telescope has released the largest near-infrared image ever taken, allowing researchers to map star-forming regions and understand how the earliest galaxies originated. This high-resolution survey will enable the identification of rare objects such as massive galaxies, highly active black holes, and colliding galaxies.
A recent genetic study found a link between height and lower risk of coronary heart disease, as well as higher risk for peripheral neuropathy and circulatory disorders. Being tall appears to protect against cardiovascular problems, but may increase the risk of non-cardiovascular conditions.
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.
A new platform and genomic database has been developed to monitor and control multidrug-resistant bacteria, with over 500 human pathogens already available. The database aims to provide strategic information on microorganisms classified as a “critical priority” by the World Health Organization.
Researchers have identified the genetic causes of three mitochondrial diseases and proposed 20 additional possibilities for further investigation using a new approach. The study provides a platform to better understand how mitochondria's hundreds of proteins work together, which could lead to improved diagnoses and treatments.
The BiCIKL Project has successfully integrated FAIR data on biodiversity for a year, focusing on creating a more transparent and efficient research ecosystem. The project aims to link different sources of biodiversity data across various infrastructures and open data platforms.
A new Regenstrief Institute study evaluates commercially available matching methodologies against real-world gold standard data to identify opportunities for improving match accuracy. The study found that referential patient matching demonstrates greater sensitivity and accuracy than traditional probabilistic approach.
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.
Alternative credit scoring systems present challenges not covered by existing regulations, leaving many Americans unable to access the credit system. These systems can be opaque and ripe for abusive lending practices, making it difficult for consumers to contest erroneous information.
Researchers developed a novel 'Wikiguideline' approach to establish medical guidelines, leveraging online collaboration and high-quality data. The method was tested using osteomyelitis, an infection of the bone, and found sufficient data for only two recommendations: increasing oral antibiotic therapy and limiting therapy duration.
A new study estimates the national economic burden of PTSD at $232.2 billion for 2018, with civilians accounting for 82% of the total costs. The study calls for increased awareness, effective therapies, and expanded evidence-based strategies to reduce the clinical and economic burden of PTSD.
A team of researchers has made a large collection of coffee samples' NMR data freely available to assess the variety under which coffee is sold. The dataset can be interactively explored using software called NMRium-browser, allowing users to visualize the molecular structure of coffee beans from different origins.
A recent study published in PLOS Biology explores the intersection of open science practices and biosecurity risks, proposing solutions to mitigate catastrophic misuse. The authors argue that controlling access to research materials and software is necessary to prevent the spread of risky information.
Researchers found a significant decline in in-hospital mortality and secondary endpoints for STEMI patients with COVID-19 in 2021 compared to 2020. Vaccination status showed zero hospital deaths among vaccinated patients, while unvaccinated patients experienced high death rates.
Researchers from North Carolina State University have released a dataset providing detailed information on COVID-19 vaccine shipments and wastage across the US. The data aims to inform modeling and decision-making to optimize vaccine supply chains.
Volunteers transcribed 130 years of handwritten rainfall observations, extending the UK's rainfall record back to 1836. The new data provides insights into extreme dry and wet months, as well as recent changes in rainfall due to climate change.
Researchers found that women are less likely to undergo common heart procedures and more likely to die in the hospital after receiving them. The study analyzed data from over 2 million hospitalizations for heart procedures between 2016 and 2019, revealing significant disparities in treatment and outcomes based on sex and race.
Researchers used a contrast pattern mining algorithm on publicly available data from 16,000 participants in the T1D Exchange Clinic Registry. The study found individuals with an immediate family history of Type 1 diabetes were more frequently diagnosed with hypertension and other co-occurring conditions.
Researchers at Rice University developed a new program called Variabel to accurately identify 'low-frequency' variants of the virus that causes COVID-19. By distinguishing true variants from sequencing errors, Variabel enables rapid characterization of within-host variation, which could aid in discovering future mutations.
A recent data-driven study by Emory University researchers highlights the struggles of US farmers to make a living, even with government subsidies. The study creates a free online data hub to track farmer livelihoods and suggests that federal subsidies need to be reimagined to support innovation and adaptation in agriculture.
GIST researchers propose a new strategy for crime prevention using artificial intelligence, trained on a large-scale dataset of deviant incident reports and corresponding images. The model, called DevianceNet, can accurately classify and detect deviant places, making it a useful tool in urban safety development.
A new approach using an array of series-connected solar cells as detectors simplifies underwater optical data links, offering a cost-effective and low-energy way to transmit data underwater. The system demonstrated the highest bandwidth ever achieved for a commercial silicon solar panel-based optical communication system.
Researchers from Argonne National Laboratory have created a set of new practices to guide the curation of high energy physics datasets, making them more FAIR and reusable. The goal is to automate the finding and use of data for humans and streamline the development of AI tools for scientific discovery.
Swine waste lagoon construction dates have been established for the first time using satellite imagery, providing insights into their environmental impact. The study focused on North Carolina and found that approximately 16% of lagoons were already in place before 1987.
Researchers from Universidad Carlos III de Madrid developed an open-source development kit (PDK) to create solutions for businesses using personal data. The tool allows companies to exploit user data in a respectful way, promoting individual control over their data.
A study by Academic Analytics Research Center found a significant increase in journal article publications (64%) and decrease in book publications (34-54%) across 12 Social Sciences disciplines from 2010 to 2020. This shift may impact library acquisitions strategies and affect humanities-related fields.
A new dataset examines publication patterns across 170 academic disciplines to provide more nuanced comparisons. The data reveals significant variation in publishing activity and venue preferences among scholars.
The HTRC will create a framework for researchers to build and implement their own tools to access the HathiTrust data more directly. The project aims to enable users to interact with the rich data extracted from the HathiTrust Digital Library's collection of over 17.5 million digitized volumes.
Editors at The BMJ argue that Covid-19 vaccine and treatment trial data should be fully available for public scrutiny. Despite the global rollout of vaccines, participant-level data remain inaccessible to doctors, researchers, and the public, sparking concerns about the lack of transparency.
Scientists have developed a mathematical method to interpret data on underground water flows, providing more efficient and accurate imaging for planning construction works and inspecting dams. The technique has great potential for locating water reservoirs in dry areas and tapping into this resource for agricultural and industrial needs.
Researchers at Oak Ridge National Laboratory have developed a retrofitted commercial refrigeration container to keep COVID-19 vaccines at ultra-low temperatures during transport. They've also identified and improved the usability of data to accelerate innovation in the bioeconomy, and investigated piezoelectric materials for radiation-...
The study estimates the risk of severe outcomes among symptomatic children aged 0-17 years in the European Union, with hospitalization rates highest among youngest age groups. The authors also note that most children with symptomatic COVID-19 have a low risk of death or hospitalization.