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MeSH Disease

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    A New Screening Method for COVID-19 MESHD based on Ocular Feature Recognition by Machine Learning Tools MESHD

    Authors: Yanwei Fu; Feng Li; Wenxuan Wang; Haicheng Tang; Xuelin Qian; Mengwei Gu; Xiangyang Xue; Evangelos Terpos; Ioannis P. Trougakos; Andreas Mentis; Markos Marangos; George Panayiotakopoulos; Meletios A. Dimopoulos; Charalampos Gogos; Alexandros Spyridonidis; Leonidas G. Alexopoulos

    doi:10.1101/2020.09.03.20184226 Date: 2020-09-10 Source: medRxiv

    The Coronavirus disease 2019 MESHD ( COVID-19 MESHD) has affected several million people. With the outbreak of the epidemic, many researchers are devoting themselves to the COVID-19 MESHD screening system. The standard practices for rapid risk screening of COVID-19 MESHD 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 MESHD patients usually accompanied by ocular manifestations consistent with the conjunctivitis MESHD conjunctivitis HP, including conjunctival hyperemia HP hyperemia MESHD, chemosis HP chemosis MESHD, epiphora HP, or increased secretions. After more than four months study, we found that the confirmed cases TRANS of COVID-19 MESHD 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 MESHD 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 MESHD, 131 pulmonary, and 68 ocular patients), as well as 136 healthy people. Remarkably, our results of COVID-19 MESHD patients in testing set consistently present similar ocular pathological symbols; and very high testing results have been achieved in terms of sensitivity SERO and specificity. We hope this study can be inspiring and helpful for encouraging more researches in this topic.

    A New Screening Method for COVID-19 MESHD based on Ocular Feature Recognition by Machine Learning Tools MESHD

    Authors: Yanwei Fu; Feng Li; Wenxuan Wang; Haicheng Tang; Xuelin Qian; Mengwei Gu; Xiangyang Xue

    id:2009.03184v1 Date: 2020-09-04 Source: arXiv

    The Coronavirus disease 2019 MESHD ( COVID-19 MESHD) has affected several million people. With the outbreak of the epidemic, many researchers are devoting themselves to the COVID-19 MESHD screening system. The standard practices for rapid risk screening of COVID-19 MESHD 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 MESHD patients usually accompanied by ocular manifestations consistent with the conjunctivitis MESHD conjunctivitis HP, including conjunctival hyperemia HP hyperemia MESHD, chemosis HP chemosis MESHD, epiphora HP, or increased secretions. After more than four months study, we found that the confirmed cases TRANS of COVID-19 MESHD 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 MESHD 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 MESHD, 131 pulmonary, and 68 ocular patients), as well as 136 healthy people. Remarkably, our results of COVID-19 MESHD patients in testing set consistently present similar ocular pathological symbols; and very high testing results have been achieved in terms of sensitivity SERO and specificity. We hope this study can be inspiring and helpful for encouraging more researches in this topic.

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