论文标题
基于机器学习工具基于眼部特征识别的Covid-19的新筛选方法
A New Screening Method for COVID-19 based on Ocular Feature Recognition by Machine Learning Tools
论文作者
论文摘要
2019年冠状病毒病(Covid-19)影响了数百万。随着流行病的爆发,许多研究人员将自己致力于Covid-19筛查系统。 COVID-19的快速风险筛查的标准实践是CT成像或RT-PCR(实时聚合酶链反应)。但是,这些方法需要专业的努力来获取CT图像和唾液样本,一定程度的等待时间,并且在某些国家 /地区最重要的是考试费。最近,一些文献表明,Covid-19患者通常伴随着与结膜炎一致的眼部表现,包括结膜性充血,化学,epiphora或分泌物增加。经过四个多月的研究,我们发现COVID-19的确认病例呈现出一致的眼病理性符号。我们提出了一种新的筛选方法,用于分析由COM CCD和CMOS摄像机捕获的眼睛区域图像,可以可靠地以非常高的精度对Covid-19进行快速风险筛选。我们认为,实施这种算法的系统应有助于分类管理或临床诊断。为了进一步评估我们的算法并获得了福丹大学上海公共卫生诊所伦理委员会的批准,我们进行了一项研究,研究了303名患者(104 Covid-19,104 Covid-19,131例肺和68名眼部患者)的眼睛区域图像,以及136名健康的人。值得注意的是,我们在测试集中的Covid-19患者的结果始终呈现出相似的眼科病理符号。并且在敏感性和特异性方面已经取得了很高的测试结果。我们希望这项研究能够鼓舞人心,并有助于鼓励在此主题中进行更多研究。
The Coronavirus disease 2019 (COVID-19) has affected several million people. With the outbreak of the epidemic, many researchers are devoting themselves to the COVID-19 screening system. The standard practices for rapid risk screening of COVID-19 are the CT imaging or RT-PCR (real-time polymerase chain reaction). However, these methods demand professional efforts of the acquisition of CT images and saliva samples, a certain amount of waiting time, and most importantly prohibitive examination fee in some countries. Recently, some literatures have shown that the COVID-19 patients usually accompanied by ocular manifestations consistent with the conjunctivitis, including conjunctival hyperemia, chemosis, epiphora, or increased secretions. After more than four months study, we found that the confirmed cases of COVID-19 present the consistent ocular pathological symbols; and we propose a new screening method of analyzing the eye-region images, captured by common CCD and CMOS cameras, could reliably make a rapid risk screening of COVID-19 with very high accuracy. We believe a system implementing such an algorithm should assist the triage management or the clinical diagnosis. To further evaluate our algorithm and approved by the Ethics Committee of Shanghai public health clinic center of Fudan University, we conduct a study of analyzing the eye-region images of 303 patients (104 COVID-19, 131 pulmonary, and 68 ocular patients), as well as 136 healthy people. Remarkably, our results of COVID-19 patients in testing set consistently present similar ocular pathological symbols; and very high testing results have been achieved in terms of sensitivity and specificity. We hope this study can be inspiring and helpful for encouraging more researches in this topic.