The Hybrid Dataset of CXR images, CT images and clinical indicators used in our article: Fast automated detection of COVID-19 from medical images using convolutional neural networks

The dataset used in our article was uploaded on our Google Drive account and the download link is provided as follows:<br>https://drive.google.com/drive/folders/1-tXCaPtv0vupjXeLvrEX2cGt3tCOqyiv?usp=sharing<br>Six compressed files (named as clinical.zip, COVID-19.zip, CXR.zip, Influenza.zip, Normal.zip and Pneumonia.zip) were included in the download address with a total size of 31.7GB.<br>The sample of this is study is a multi-modal dataset consisting of X-ray image data (X-data), CT image data (CT-data) and clinical indicators data (Clinical-data).The X-data of COVID-19 cases collected from the CCD contained 212 patients diagnosed with COVID-19. We also collected 5,100 normal cases and 3,100 pneumonia cases from the RSNA. In addition, The X-data collected from the Youan hospital contained 45 cases diagnosed with COVID-19, 503 normal cases, 435 cases diagnosed with pneumonia(not COVID-19 patients), and 145 cases diagnosed as influenza.We collected CT-data of 120 normal cases from the LUNA-16. We also collected the CT-data of 215 pneumonia cases from the ICNP. The CT-data collected from the Youan hospital contained 95 patients diagnosed with COVID-19, 50 patients diagnosed with influenza and 215 patients diagnosed with pneumonia.The Clinical-data contained 95 clinical indicators data pairs of COVID-19 (369 images of the lesion area and 95×5 clinical indicators).<br>The persistent web links for the four public data repositories are listed as below: CCD: (https://github.com/ieee8023/covid-chestxray-dataset) RSNA: (https://www.kaggle.com/c/rsna-pneumonia-detection-challenge) LUNA16: (https://luna16.grand-challenge.org/Data/) ICNP: (https://data.mendeley.com/datasets/kk6y7nnbfs/1)<br>