Tlevision was Spain's medium of choice for reliable news and information about the coronavirus (COVID-19) outbreak according to a survey conducted in March 2020. This study reveals that 85 percent of Spaniards use this channel to keep up to speed on the latest updates about the outbreak, whereas only 13 percent read print press for the same purpose.

This statistic illustrates the percentage of population that found false or misleading news about the coronavirus in Spain in **********, by source of information and political ideology. As of that date, almost half of the population that positioned themselves on the left spectrum believed that false or misleading information about the coronavirus pandemic spread through people the did not know personally.

The project’s main aim is to explore the discursive functions of similes used to communicate the fist waves of Covid-19 pandemic in digital newspapers in 2020. The dataset includes 200 news items (100 English and 100 Spanish) containing both the string ‘TARGET is like SOURCE’ where virus or coronavirus is either the target, that is, the concept that is described (‘(CORONA)VIRUS is like X’), or the source, i.e. the concept that lends its properties for another, usually more abstract, one (‘X is like A VIRUS’).

#New version (4) has been released in 12-01-2022: The update includes the lung masks for all X-ray images.

A team of researchers from Qatar University, Doha, Qatar and the University of Dhaka, Bangladesh have created a database of posterior-to-anterior (PA) or anterior-to-posterior (AP) X-rays images for COVID-19, Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS). Currently, the database includes 423 positive COVID-19 images, 134 positive SARS images and 144 positive MERS images with the corresponding lung masks.

Image Formats - All the images are in Portable Network Graphics (PNG) file format.

Objective Researchers can use this database to produce useful and impactful scholarly work on COVID-19, which can help in tackling this pandemic.

Citation Please cite the following paper if you used this dataset

Tahir, A., Qiblawey, Y., Khandakar, A. et al. Deep Learning for Reliable Classification of COVID-19, MERS, and SARS from Chest X-ray Images. Cogn Comput (2022). https://doi.org/10.1007/s12559-021-09955-1

Also Cite this dataset as following @misc{yazan qiblawey_muhammad chowdhury_anas Tahir_amith khandakar_tawsifur rahman_uzair khurshid_2020, title={COVID-19, SARS, MERS X-ray Images Dataset}, url={https://www.kaggle.com/dsv/1572508}, DOI={10.34740/KAGGLE/DSV/1572508}, publisher={Kaggle}, author={Yazan Qiblawey and Muhammad Chowdhury and Anas Tahir and Amith Khandakar and Tawsifur Rahman and Uzair Khurshid}, year={2020} }

Acknowledgments Thanks to Italian Society of Medical and Interventional Radiology (SIRM) COVID-19 Database [1], Novel Corona Virus 2019 Dataset, Radiopaedia, Chest Imaging (Spain) at thread reader and online articles and news-portals (until April 16th), SIRM COVID-19 database, Joseph Paul Cohen et al.[2] database.

References [1] S.I. S. o. M. a. I. Radiology. (2020). COVID-19 Database. Available: https://www.sirm.org/category/senza-categoria/covid-19/ [2] Joseph Paul Cohen and Paul Morrison and Lan Dao, "COVID-19 image data collection", arXiv:2003.11597, 2020 https://github.com/ieee8023/covid-chestxray-dataset.

Coronavirus a nivel diario - Personas con pauta completa de la vacuna por cada 0 habitantes para Andalucía, Aragón, Asturias, Islas Baleares, Canarias, Cantabria, Castilla y León, Castilla-La Mancha, Cataluña, Comunidad Valenciana, Extremadura, Galicia, La Rioja, Madrid, Murcia, Navarra, País Vasco, Ceuta, Melilla como comunidad autónoma

Trasplantes a nivel anual - Número de donantes para total como grupo de edad del donante y España como país