COVID Data for Shared Learning (CDSL): A comprehensive, multimodal COVID-19 dataset from HM Hospitales

COVID Data for Shared Learning (CDSL) is a multimodal database comprising de-
identified medical data from 4,479 patients who were hospitalized with
confirmed or suspected COVID-19 in the Spanish 'HM Hospitales' group from
2019-12-26 to 2021-02-13. The database provides tabular demographic,
diagnostic, clinical and treatment information, as well as radiological images
in JPG format, namely chest X-ray and computed tomography scans. The primary
goal of CDSL is to develop a comprehensive toolkit to support researchers and
institutions in building multimodal models for prediction, classification and
optimization. CDSL database was promptly shared with the international
research community at the onset of the COVID-19 pandemic to promote worldwide
collaboration and, ultimately, guide policy decisions and facilitate effective
response efforts studies on the disease.

共享学习用COVID数据集（COVID Data for Shared Learning, CDSL）是一个多模态数据库，收录了2019年12月26日至2021年2月13日期间，西班牙“HM Hospitales”医疗集团内4479名因确诊或疑似感染COVID-19住院患者的去标识化医疗数据。该数据库包含结构化的人口统计学、诊断学、临床及治疗相关信息，以及JPG格式的放射影像资料，具体涵盖胸部X线片与计算机断层扫描图像。CDSL的核心目标是开发一套综合工具集，以支持研究人员与科研机构构建用于预测、分类及优化任务的多模态模型。该数据集于新冠疫情暴发初期即向国际科研共同体公开共享，旨在推动全球科研协作，最终为疾病防控政策制定提供参考，并助力高效抗疫相关研究工作。

搜集汇总

背景与挑战

背景概述

COVID Data for Shared Learning (CDSL) 是一个来自西班牙HM Hospitales集团的多模态COVID-19数据集，包含4479名在2019年12月至2021年2月期间住院的确诊或疑似患者的去识别化医疗数据。该数据集综合了表格化的人口统计、诊断、临床和治疗信息，以及超过144万张以JPG格式提供的胸部X光和CT扫描放射学图像，旨在支持研究人员构建多模态预测和分类模型。