<p>This dataset contains news stories related to Covid-19 pandemic fact-checked by expert fact-checkers.&nbsp;</p>

Instructions: 

Data is in .csv files and contains the news article with the corresponding fake rating from USA, India, and Europe.

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108 Views

Reverse transcription-polymerase chain reaction (RT-PCR) is currently the gold standard in COVID-19 diagnosis. It can, however, take days to provide the diagnosis, and false negative rate is relatively high. Imaging, in particular chest computed tomography (CT), can assist with diagnosis and assessment of this disease. Nevertheless, it is shown that standard dose CT scan gives significant radiation burden to patients, especially those in need of multiple scans.

Instructions: 

 

“Dataset-S1” contains two folders for COVID-19 and Normal DICOM images, named as “COVID-S1” and “Normal-S1”, respectively. Within the same folder, three CSV files are available. The first one, named as “Radiologist-S1.csv”, contains labels assigned to the corresponding cases by three experienced radiologists. The second CSV file, “Clinical-S1.csv”, includes the clinical information as well as the result of the RT-PCR test, if available. The third file is named “LDCT-SL-Labels-S1.csv” and contains the slice-level labels related to COVID-19 cases. In other words, slices demonstrating infection are specified in this file.

Each row in this CSV file corresponds to a specific case, and each column represents the slice number in the volumetric CT scan. Label 1 indicates a slice with the evidence of infection, while 0 is assigned to slices with no evidence of infection.

Note that slices in each case should be sorted based on the “Slice-Location” value to match with the provided labels in the CSV file. The Slice Location values are stored in DICOM files and accessible from the following DICOM tag: (0020,1041) – DS – Slice Location

 “Dataset-S2” contains 100 COVID-19 positive cases, confirmed with RT-PCR test. 68 cases have related imaging findings, whereas 32 do not reveal signs of infection. These two groups are placed in two folders of “PCP-Lung-Positive “and “PCP-Lung-Negative”. “Dataset-S2” also includes a CSV file, namely “Clinical-S2.csv” presenting the clinical information.

 

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The dataset consists of two classes: COVID-19 cases and Healthy cases 

Instructions: 

Unzip the dataset

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329 Views

We delicately designed, collected and labelled a realistic audio dataset containing recordings of patients with respiratory diseases, named the Corp Dataset. 168 hours of recordings with 9969 coughs from 42 different patients are included. The dataset is published online on the MARI Lab website (https://mari.tongji.edu.cn/info/1012/1030.htm).

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This datasets contains Xrays of positive COVID-19 and Pneumonia patients.

For the COVID-19 class, three sources were used in this work, BIMCV-COVID-19+ (Spain), COVID-19- AR (USA) and V2-COV19-NII (Germany).

 

  

The pneumonia class data came from 3 sources: (i) the National Institute of Health (NIH) dataset, (ii) Chexpert dataset and (iii) Padchest dataset.

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245 Views

 Lung segmentation is essential in developing AI-assisted diagnosis methods. Here is the result of lung segmentation using morphological operation, and it has been used in our study. It contains 7053 CT slices in .jpg format. And the original dataset can be seen via  the Kaggle link https://www.kaggle.com/hgunraj/covidxct

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212 Views

The dataset collects the results of a survey of 325 respondents. Each respondent is asked to design a route from an origin to a destination taking into account the following considerations:

  • The route should avoid crowds to avoid getting COVID-19.
  • They should take into account the context provided: day, time, month, holiday period.

A total of 10 scenarios located in the city of Ciudad Real were designed.

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215 Views

The Ways To Wear a Mask or a Respirator Database (WWMR-DB) is a test database that can be used to compare the behavior of current mask detection systems with images that most closely resemble the real case. It consists of 1222 images divided into 8 classes, depicting the most common ways in which masks or respirators are worn:

- Mask Or Respirator Not Worn

- Mask Or Respirator Correctly Worn

- Mask Or Respirator Under The Nose

- Mask Or Respirator Under The Chin

- Mask Or Respirator Hanging From An Ear

- Mask Or Respirator On The Tip Of The Nose

Instructions: 

For any question, please send an email to antonio.marceddu@polito.it.

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506 Views

This dataset has been developed based on the work of the GeoCOV19Tweets Dataset. The original work by Lamsal, R. runs network analysis on a similar dataset to understand the underlying relationship between countries and hashtags. The work did an analysis on roughly 300k number of [country, hashtag] relations from 190 countries and territories, and 5055 unique hashtags. This work pushes the number of relationships by 3 times.

Instructions: 

This dataset provides [place, hashtag] relationships in a Comma-separated values (CSV) file. Each line represents a relationship. You can simply use the CSV file as per your research needs.

However, if you need to change the place entity from city (currently the dataset uses ["place"]["name"] object) to country, you'll have to consider the ["place"]["country"] object instead. The sample script is provided with this dataset. The script takes in a list of tweet IDs present in a CSV file and hydrates the IDs to extract places and hashtags relationships. The script is written for twarc.

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2229 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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131 Views

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