Lung CT COVID-19 batch 1

<p>This data set is part of the public development data for&nbsp;the&nbsp;<a href="http://auc23.grand-challenge.org/">2023 Automated Universal Classification Challenge</a> (AUC23). The data set concerns&nbsp;COVID-19 RT-PCR outcome prediction and prediction of severe COVID-19, defined as death or intubation after one month, from computed tomography (CT). The data set was previously introduced and described by <a href="https://pubs.rsna.org/doi/full/10.1148/radiol.2021210384">Revel, M. et al (2021)</a>. Data was&nbsp;restructured in compliance with the&nbsp;<a href="https://auc23.grand-challenge.org/">AUC23</a>&nbsp;challenge format.&nbsp;The STOIC project collected CT&nbsp;images of 10,735 individuals suspected of being infected with SARS-COV-2 during the first wave of the pandemic in France, from March to April 2020. For each patient in the training set, the dataset contains binary labels for COVID-19 presence based on RT-PCR test results, and COVID-19 severity, defined as intubation or death within one month from the acquisition of the CT scan. This data set contains the training sample of the STOIC dataset as used in the <a href="https://stoic2021.grand-challenge.org/">STOIC2021</a>&nbsp;challenge.</p> <p>Images are&nbsp;3D tensors:</p> <ul> <li>0:&nbsp;3D CT scan</li> </ul> <p>Classification labels:</p> <ul> <li>COVID-19: <ul> <li>0: Negative RT-PCR</li> <li>1: Positive RT-PCR<br> &nbsp;</li> </ul> </li> <li>Severe&nbsp;COVID-19: <ul> <li>0:&nbsp;Alive and no intubation after one month</li> <li>1: Death or intubation after one month</li> </ul> </li> </ul> <p>imagesTr (root folder with all patients and studies)<br> &nbsp; &nbsp; ├── covid19severity_6_0000.mha &nbsp;(3D CT&nbsp;for study 6)<br> &nbsp;&nbsp; &nbsp;├── covid19severity_17_0000.mha &nbsp;(3D CT&nbsp;for study 17)<br> &nbsp; &nbsp; ├──&nbsp;...</p> <p>Please cite the following article if you are using the <a href="https://registry.opendata.aws/stoic2021-training/">STOIC2021 training dataset</a>:</p> <pre><code>STOIC2021 Training was accessed on DATE from https://registry.opendata.aws/stoic2021-training. STOIC2021 Training was documented in Thoracic CT in COVID-19: The STOIC Project, Revel, Marie-Pierre, et al. Radiology, 2021, https://doi.org/10.1148/radiol.2021210384.</code></pre> <p>Due to upload&nbsp;size limits, the data set was split into six batches.</p> <p>Batch 2:&nbsp;<a href="https://zenodo.org/record/8042589">https://zenodo.org/record/8042589</a></p> <p>Batch 3:&nbsp;<a href="https://zenodo.org/record/8042817">https://zenodo.org/record/8042817</a></p> <p>Batch 4:&nbsp;<a href="https://zenodo.org/record/8043089">https://zenodo.org/record/8043089</a></p> <p>Batch 5:&nbsp;<a href="https://zenodo.org/record/8043216">https://zenodo.org/record/8043216</a></p> <p>Batch 6:&nbsp;<a href="https://zenodo.org/record/8043218">https://zenodo.org/record/8043218</a></p>