We achieved the classification of COVID-19 CT scans and non-COVID-19 CT scans and analyzed the development of the patients' condition through the CT scans. The average accuracy rate is 96.7%, sensitivity is 95.2%, and F1 score is 95.9%. Each scan takes about 30 seconds for detection. ...
In this section, we introduce the pixel-level labeled COVID-19 CT dataset along with theCOVID-Ratesegmentation framework that takes thick-slice chest CT images of confirmed COVID-19 patients and automatically segments regions of COVID-19 infection. Figure2illustrates the overall pipeline of theCO...
In March 2020, the Asia Pacific Gender in Humanitarian Action Working Group recommended that all states in the Asia Pacific needed to prioritise the collection of disaggregated data related to the outbreak by “sex, age, and disability”; and this data needed to be analysed in order to “under...
To date (December 29th 2020), more than 79 million confirmed cases have been reported in over 200 countries and territories, with a mortality rate of 2.2% [1]. Considering the pandemic of COVID-19, early detection and treatment are of great importance to the slowdown of viral transmission ...
According to the WHO, as of March 6, 2020, so in just the first three months of the outbreak, there have been 100,685 cases of COVID-19 and 3,411 deaths, that works out to a mortality rate of 3.4%. On top of that, every case of COVID-19, leads to roughly 2.3 new cases, ...
It achieved an accuracy rate of 99.9% for the first dataset, 60% for the second and 50.1% for the third. Gao et al. [23] used a total of 1918 CT scans in their study where they developed an approach called double-branched combination network (DCN) with less attention module for Co...
The existing works mainly focused on detecting COVID-19 using CT or X-ray images against either radiology or NAT. Given the relatively higher false-negative rate of NAT in asymptomatic detection, the prediction results only against NAT might have biases. More seriously, though people with NAT-ne...
Regarding the choice of hyperparameters, we used the stochastic gradient descent (SGD) and set the learning rate at 0.003, the momentum at 0.9, and the batch size at 64. RGB reordering was applied, and the final input to the proposed model was provided as \(512 \times 512 \times 3\)...
Xu X [28] exhibited that the traditional method used for identifying COVID-19 has low positive rate during initial stages. He developed a model which does the early screening of CT images. Yoon SH [31] found that the COVID-19 pneumonia that affected people in Korea exhibits similar ...
According to iFlytek, the system can read and analyze a patient's CT scans within three seconds. Deployed at a hospital in Hefei, Anhui Province, the system so far has identified all confirmed cases and has a recall rate of 90 percent in lesion detection. ...