基于人工智能的胸部 CT 图像新冠肺炎诊断研究进展
Review on Diagnosis of COVID-19 from Chest CT Images Using Artificial Intelligence.
机构信息
Department of Biomedical Engineering, Near East University, Nicosia / TRNC, Mersin-10, 99138, Turkey.
DESAM Institute, Near East University, Nicosia / TRNC, Mersin-10, 99138, Turkey.
出版信息
Comput Math Methods Med. 2020 Sep 26;2020:9756518. doi: 10.1155/2020/9756518. eCollection 2020.
The COVID-19 diagnostic approach is mainly divided into two broad categories, a laboratory-based and chest radiography approach. The last few months have witnessed a rapid increase in the number of studies use artificial intelligence (AI) techniques to diagnose COVID-19 with chest computed tomography (CT). In this study, we review the diagnosis of COVID-19 by using chest CT toward AI. We searched ArXiv, MedRxiv, and Google Scholar using the terms "deep learning", "neural networks", "COVID-19", and "chest CT". At the time of writing (August 24, 2020), there have been nearly 100 studies and 30 studies among them were selected for this review. We categorized the studies based on the classification tasks: COVID-19/normal, COVID-19/non-COVID-19, COVID-19/non-COVID-19 pneumonia, and severity. The sensitivity, specificity, precision, accuracy, area under the curve, and F1 score results were reported as high as 100%, 100%, 99.62, 99.87%, 100%, and 99.5%, respectively. However, the presented results should be carefully compared due to the different degrees of difficulty of different classification tasks.
COVID-19 的诊断方法主要分为两类，基于实验室的方法和胸部 X 射线方法。过去几个月见证了越来越多的研究使用人工智能 (AI) 技术结合胸部计算机断层扫描 (CT) 来诊断 COVID-19。在本研究中，我们回顾了使用胸部 CT 进行 AI 诊断 COVID-19 的方法。我们使用了“深度学习”、“神经网络”、“COVID-19”和“胸部 CT”等术语，在 ArXiv、MedRxiv 和 Google Scholar 上进行了搜索。截至 2020 年 8 月 24 日，已经有近 100 项研究，其中 30 项研究被选入本次综述。我们根据分类任务对这些研究进行了分类：COVID-19/正常、COVID-19/非 COVID-19、COVID-19/非 COVID-19 肺炎和严重程度。报告的敏感性、特异性、精确性、准确性、曲线下面积和 F1 评分结果分别高达 100%、100%、99.62%、99.87%、100%和 99.5%。然而，由于不同分类任务的难度程度不同，应仔细比较这些结果。
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