The COVID-19 pneumonia is a global threat since it emerged in early December 2019. Driven by the desire to develop a computer-aided system for the rapid diagnosis of COVID-19 to assist radiologists and clinicians to combat with this pandemic, we retrospectively collected 206 patients with positive reverse-transcription polymerase chain reaction (RT-PCR) for COVID-19 and their 416 chest computed tomography (CT) scans with abnormal findings from two hospitals, 412 non-COVID-19 pneumonia and their 412 chest CT scans with clear sign of pneumonia are also retrospectively selected from participating hospitals. Based on these CT scans, we design an artificial intelligence (AI) system that uses a multi-scale convolutional neural network (MSCNN) and evaluate its performance at both slice level and scan level. Experimental results show that the proposed AI has promising diagnostic performance in the detection of COVID-19 and differentiating it from other common pneumonia under limited number of training data, which has great potential to assist radiologists and physicians in performing a quick diagnosis and mitigate the heavy workload of them especially when the health system is overloaded. The data is publicly available for further research at https://data.mendeley.com/datasets/3y55vgckg6/1https://data.mendeley.com/datasets/3y55vgckg6/1.

自从2019年12月上旬出现以来，COVID-19肺炎一直是全球性威胁。出于对开发计算机辅助系统以快速诊断COVID-19的愿望的驱动，我们需要回顾性收集这些数据以帮助放射科医生和临床医生应对这种流行病206例COVID-19的逆转录聚合酶链反应（RT-PCR）阳性的患者及其416例胸部计算机断层扫描（CT）扫描发现两家医院有异常发现，412例非COVID-19肺炎和412例胸部CT扫描发现异常还回顾性地从参与的医院中选择了明显的肺炎征象。基于这些CT扫描，我们设计了一个使用多尺度卷积神经网络（MSCNN）的人工智能（AI）系统，并在切片级别和扫描级别上评估了其性能。实验结果表明，在有限数量的训练数据下，拟议的AI在检测COVID-19并将其与其他常见的肺炎区别开来方面具有有希望的诊断性能，这在协助放射科医生和医生进行快速诊断并减轻重症患者方面具有巨大的潜力。它们的工作量，特别是在卫生系统超负荷的情况下。该数据可通过https://data.mendeley.com/datasets/3y55vgckg6/1https://data.mendeley.com/datasets/3y55vgckg6/1公开获取，以进行进一步研究。它具有巨大的潜力，可以帮助放射科医生和医师进行快速诊断并减轻他们的繁重工作量，尤其是在卫生系统超负荷的情况下。该数据可通过https://data.mendeley.com/datasets/3y55vgckg6/1https://data.mendeley.com/datasets/3y55vgckg6/1公开获取，以进行进一步研究。它具有巨大的潜力，可以帮助放射科医生和医师进行快速诊断并减轻他们的繁重工作量，尤其是在卫生系统超负荷的情况下。该数据可通过https://data.mendeley.com/datasets/3y55vgckg6/1https://data.mendeley.com/datasets/3y55vgckg6/1公开获取，以供进一步研究。