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267 results for “COVID19”
Covid19 case data November 2020 - The Netherlands
<p>This data is the daily case data on covid-19 cases in the Netherlands, published by the RIVM (national public health agency). The data covers all case data of November 2020.</p>
Covid19 case data August 2020
<p>This data is the daily case data on covid-19 cases in the Netherlands, published by the RIVM (national public health agency). The data covers all case data of August 2020.</p>
Covid19 case data July 2020
<p>This data is the daily case data on covid-19 cases in the Netherlands, published by the RIVM (national public health agency). The data covers all case data of July 2020.</p>
U-10: United-10 COVID19 CT Dataset
<p>This dataset supports the research detailed in the pre-print "<a href="https://arxiv.org/abs/2308.09730"><strong>Virtual Imaging Trials Improved the Transparency and Reliability of AI Systems in COVID-19 Imaging</strong></a>." The study employs both clinical and simulated CT data to evaluate AI models for COVID-19 diagnosis. By leveraging the Virtual Imaging Trials (VIT) framework, the research addresses reproducibility and generalizability issues prevalent in medical imaging AI models. <br><br><strong>The dataset includes:</strong></p> <ul> <li><strong>Clinical CT Data:</strong> Drawn from 10 publicly available datasets, comprising over 12,000 volumes. These datasets span diverse populations, imaging protocols, and scanner configurations. Each of the 10 zip files contains pre-processed CT TFRecords (Train/Validation/Test) used in the study. Detailed information about the data sources, pre-processing steps, and the inclusion and exclusion criteria can be found in the manuscript (<a href="https://arxiv.org/abs/2308.09730">https://arxiv.org/abs/2308.09730</a>).</li> <li><strong>Simulated CT Data:</strong> Generated using computational anatomical phantoms from the XCAT model and imaged with the DukeSim simulation framework. This synthetic dataset allows controlled experiments that isolate the effects of imaging physics and patient-specific factors. Can be available upon request through Center For virtual Imaging Trial Portal at <a href="https://cvit.duke.edu/">https://cvit.duke.edu/</a></li> </ul> <p>The accompanying study analyzes the performance of lightweight convolutional neural networks on both real and synthetic data, comparing results across multiple internal and external validation scenarios. Insights into factors such as infection severity, imaging dose, and modality type are explored.</p> <p><strong>For further details, visit our Project Page:</strong> <a href="https://fitushar.github.io/ReviCOVID.github.io/">https://fitushar.github.io/ReviCOVID.github.io/</a><br>The full source code is available on gitHub and GitLab<br><strong>GitHub:</strong> <a href="https://github.com/fitushar/CVIT_ReviCOVID19">https://github.com/fitushar/CVIT_ReviCOVID19</a><br><strong>GitLab :</strong> <a href="https://gitlab.oit.duke.edu/cvit-public/cvit_revicovid19">https://gitlab.oit.duke.edu/cvit-public/cvit_revicovid19</a></p> <p><strong>Citation:</strong> When using this dataset, please cite the manuscript () and the original data-source.<br><strong><em>Tushar et al.</em>, "Virtual Imaging Trials Improved the Transparency and Reliability of AI Systems in COVID-19 Imaging", arXiv:2308.09730.</strong></p> <p><strong>Contact:</strong> fakrulislam.tushar@duke.edu</p>
DATA OF THE TELEPSY-COVID19 PROJECT
<p>The data were collected and processed during the COVID pandemic in the framework of a free psychological teleconsulting called TELEPSY-COVID19 made available by SIMP Italian Society of Psychosomatic Medicine.</p>
Corresponding spreadsheet to the Paper 'Comparative analysis of pre-Covid19 child immunization rates across 30 European countries and identification of underlying positive societal and system influences'
<p>This study provides a macro-level societal and health system focused analysis of child vaccination rates in 30 European countries, exploring the effect of context on coverage. The importance of demography and health system attributes on health care delivery are recognized in other fields, but generally overlooked in vaccination. The analysis is based on correlating systematic data built up by the Models of Child Health Appraised (MOCHA) Project with data from international sources, so as to exploit a one-off opportunity to set the analysis within an overall integrated study of primary care services for children, and the learning opportunities of the ‘natural European laboratory’. The descriptive analysis shows an overall persistent variation of coverage across vaccines with no specific vaccination having a low rate in all the EU and EEA countries. However, contrasting with this, variation between total uptake per vaccine across Europe suggests that the challenge of low rates is related to country contexts of either policy, delivery, or public perceptions. Econometric analysis aiming to explore whether some population, policy and/or health system characteristics may influence vaccination uptake provides important results - GDP per capita and the level of the population’s higher education engagement are positively linked with higher vaccination coverage, whereas mandatory vaccination policy is related to lower uptake rates. The health system characteristics that have a significant positive effect are a cohesive management structure; a high nurse/doctor ratio; and use of practical care delivery reinforcements such as the home-based record and the presence of child components of e‑health strategies.</p>
Multimodal dataset: Protein Function Prediction using STRING data & COVID19 Mortality Model by EI
<p>The PFP.zip file contains 1. 5 well-formated GO terms dataset for EI, 2. STRING data 3. GO term annotation. The last two could be merged by the 'generate_data.py' script in https://github.com/GauravPandeyLab/ensemble_integration</p> <p>The covid19_model_built.zip contained the EI model built based on the COVID-19 Mortality dataset, the detail of usage are here:.</p>
Covid19-twitter dataset
<p>Here, we provide the <em><strong>tab-separated values (tsv)</strong></em> version of the dataset. The first line contains the column names and each subsequent line contains features of an instance of the dataset. Features are separated by a tab character ("/t").</p>
COVID19 vaccination choice among Iraqi students at Al-Zahraa University for women
<p>198 first-year students in the Department of Anesthesia at University of Al-Zahra participated in this cross-sectional questionnaire-based study. A Google Classroom event was attended by 198 students resulting in a response rate of (100 %). This research study was analytical in nature. The questionnaire was created by the researcher, and a few questions were adapted from other studies and incorporated into the questionnaire. Ethical approval was granted by the independent ethics committee of Al-Zahra University in Karbala-Iraq prior to the research. The period of research and data collection was between Feb. 2021 and August 2021. Questionnaires were distributed among the students using Google Classroom and were returned by the students after completion via the same method. The responses were retrieved as an excel file from the google form a questionnaire and imported into SPSS version.23 to be analyzed and frequencies and percentages determined. The questionnaire is related to COVID19 vaccination preference. The questionnaire is comprised of four tables with eight questions. Statistical tests used frequency and rates.</p>
COVID19 Flow-Maps Daily-Mobility for Spain
<p>This data-set contains daily aggregations of the hourly data provided by MITMA, aggregated at different levels of spatial resolution.</p> <p><strong>Maestra 1: Origin-Destination matrix for the mobility layer, with hourly resolution</strong> Each entry has a date and time period (the range between two consecutive hours), the origin and destination zones and the number of trips from origin to destination. Origin and destination zones correspond to geometries from the MITMA mobility layer and internal trips (same layer of origin and destination) are also reported.</p> <p><strong>Maestra 2: Trips per person matrix on each mobility area on a daily basis.</strong> This indicator reports population-based daily mobility behavior. For each date and zone from the MITMA mobility layer, the indicator reports how many persons have performed 0, 1, 2 or more than 2 trips. While the indicator does not provide the destination of the trips, it accounts for the fractions of people performing at least one trip or none, as well as the estimated total population in that zone for the given date (considering as population those persons who stay overnight in the zone on that date).</p> <p>Original data records come from a study conducted by the MITMA, which analyses the mobility and distribution of the population in Spain from February 14th 2020 to May 9th 2021. The study is based on a sample of more than 13 million anonymised mobile phone lines provided by a single mobile operator whose subscribers are evenly distributed.</p> <p>For more information visit: <a href="https://flowmaps.life.bsc.es/flowboard/data">https://flowmaps.life.bsc.es/flowboard/data</a> and <a href="https://www.mitma.gob.es/ministerio/covid-19/evolucion-movilidad-big-data">https://www.mitma.gob.es/ministerio/covid-19/evolucion-movilidad-big-data</a>.</p>
Zilucoplan® in Improving Oxygenation, Short-, Longterm Outcome of COVID19 Patients With Acute Hypoxic Respiratory Failure
ClinicalTrials.gov study NCT04382755. IPD Sharing: NO. Countries: 1. Publications: 2.
Reparixin add-on Therapy to Std Care to Limit Progression in Pts With COVID19 & Other Community Acquired Pneumonia
ClinicalTrials.gov study NCT05254990. IPD Sharing: Not stated. Countries: 7. Publications: 1.
IFN-beta 1b and Remdesivir for COVID19
ClinicalTrials.gov study NCT04647695. IPD Sharing: YES. Countries: 1. Publications: 8.
RAS and Coagulopathy in COVID19
ClinicalTrials.gov study NCT04419610. IPD Sharing: NO. Countries: 1. Publications: 1.
Transmission of Coronavirus Disease 2019 (COVID19) in Crowded Environments
ClinicalTrials.gov study NCT05119348. IPD Sharing: NO. Countries: 1. Publications: 1.
COVID19 OutcomeS in Myeloma and the Impact of VaCcines
ClinicalTrials.gov study NCT05831787. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Inhaled Ciclesonide for Outpatients With COVID19
ClinicalTrials.gov study NCT04435795. IPD Sharing: NO. Countries: 1. Publications: 1.
Autoantibody discovery across monogenic, acquired, and COVID19-associated autoimmunity with scalable PhIP-Seq
Open the record for dataset details and reuse information.
DISPLAYING THE COVID19 ECONOMIC PROSPECTS 2020 & 2021 of IMF
<p>Displaying real GDP growth from 2017 to 2021 according to IMF data allows us to quickly assess the global economic impact of the COVID19</p>
DATASET THE COVID19 ECONOMIC PROSPECTS 2020 & 2021 of IFM
<p>Dataset in excel of main macroeconomic indicators growth from 2017 to 2021 for near 200 countries and according to IMF data. It allows us to quickly assess the impact of the COVID19 in the global economic</p> <p>It includes: real GDP growth, GDP per capita, inflation, unemployment rate, general government net lending /borrowing.</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.