Este conjunto de datos es el resultado de un instrumento de medición aplicado para el desarrollo del proyecto "Aplicación de técnicas de minería de datos para la caracterización de estudiantes bajo el efecto de la pandemia de COVID-19".

En dicho instrumento se recolectaron datos sobre de variables sociodemográficas, económicas, condiciones técnicas referentes a la educación a distancia, salud emocional, así como académicas de estudiantes de un programa educativo de la Universidad Autónoma del Estado de Hidalgo.

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COVID-19 tracing data are utilized to form two dataset networks, one is based on the virus transition between the world countries, as the dataset consists of 36 countries and 75 relationships between them. Whereas the other dataset is an attributed network based on the virus transition among the contact tracing in the Kingdom of Bahrain. This type of networks that is concerned in tracking a disease or virus was not formed based on COVID-19 virus transmission.

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610 Views

This dataset contains world news related to Covid-19 and vaccine and also with the news article's available metadata.

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434 Views

People turn to search engines and social media to seek information duringpopulation-level events, such as during civil unrest, disease outbreaks, fires, or flood.They also tend to participate in discussions and disseminate information and opinionsvia social media forums, and smartphone messaging applications. COVID-19 pandemicwas not any different. However, the proper medical awareness and correct informationdissemination is critical during a pandemic.

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435 Views

A dataset contains a total of 578,375 COVID-19 confirmed cases reported in Thailand that were being recorded between 22 January 2021 to 30 July 2021.

Daily reports of the COVID-19 situation in Thailand can be download from https://data.go.th/en/dataset/covid-19-daily.

Resource ID: 87abdf57-7edd-4864-9766-7bb0e87272f9

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170 Views

BIMCV-COVID19- dataset is a large dataset with chest X-ray images CXR (CR, DX) and computed tomography (CT) imaging of no COVID-19 patients along with their radiographic findings, pathologies, polymerase chain reaction (PCR), immunoglobulin G (IgG) and immunoglobulin M (IgM) diagnostic antibody tests and radiographic reports from Medical Imaging Databank in Valencian Region Medical Image Bank (BIMCV).

Instructions: 

Once all the compressed files have been downloaded, use 00_extract_data.sh for their correct decompression. For more information, you could see the links on this page.

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383 Views

BIMCV-COVID19+ dataset is a large dataset with chest X-ray images CXR (CR, DX) and computed tomography (CT) imaging of COVID-19 patients along with their radiographic findings, pathologies, polymerase chain reaction (PCR), immunoglobulin G (IgG) and immunoglobulin M (IgM) diagnostic antibody tests and radiographic reports from Medical Imaging Databank in Valencian Region Medical Image Bank (BIMCV).

Instructions: 

Once all the compressed files have been downloaded, use 00_extract_data.sh for their correct decompression. For more information, you could see the links on this page

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785 Views

This data resource is an outcome of the NSF RAPID project titled "Democratizing Genome Sequence Analysis for COVID-19 Using CloudLab" awarded to University of Missouri-Columbia.

The resource contains the output of variant analysis (along with CADD scores) on human genome sequences obtained from the COVID-19 Data Portal. The variants include single nucleotide polymorphisms (SNPs) and short insert and deletes (indels).

Instructions: 

1. Download a .zip file.

2. Unzip the file and extract it into a folder. 

3. There will be two folders, namely, VCF and CADD_Scores. These folders contain the compressed .vcf and .tsv files. The .vcf files are filtered VCF files produced by the GATK best practice workflow for RNA-seq data. The reference genome hg19 was used. There is also a .xlsx file containing the run accession IDs (e.g., SRR12095153) and URLs (e.g., https://www.ebi.ac.uk/ena/browser/view/SRR12095153) from where the paired end sequences were downloaded. Complete description of the sequences can be found via these URLs.

4. Check for new .zip files.

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945 Views

The dataset contains the data on ICU-transferred (N=100) and Stable (N=131) patients with COVID-19 (N=156) and Non-COVID-19 viral pneumonia (N=75). Among COVID-19 patients of this study, 82 patients developed Refractory Respiratory Failure (RRF) or Severe Acute Respiratory Distress Syndrome (SARDS) and were transferred to Intensive Care Unit (ICU), 74 patients had a Stable course of disease and were not transferred to ICU.

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580 Views

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