TY - JOUR AU - Dong, Dawei AU - Luo, Zujin AU - Zheng, Yue AU - Liang, Ying AU - Zhao, Pengfei AU - Feng, Linlin AU - Wang, Dawei AU - Cao, Ying AU - Zhao, Zhenhao AU - Ma, Yingmin PY - 2022/11/29 Y2 - 2024/03/29 TI - Application of deep learning-based diagnostic systems in screening asymptomatic COVID-19 patients among oversea returnees JF - The Journal of Infection in Developing Countries JA - J Infect Dev Ctries VL - 16 IS - 11 SE - Coronavirus Pandemic DO - 10.3855/jidc.15022 UR - https://jidc.org/index.php/journal/article/view/36449642 SP - 1706-1714 AB - <p>Introduction: Our study aimed to investigate the performance of deep learning (DL)-based diagnostic systems in alerting against COVID-19, especially among asymptomatic individuals coming from overseas, and to analyze the features of identified asymptomatic patients in detail.</p><p>Methodology: DL diagnostic systems were deployed to assist in the screening of COVID-19, including the pneumonia system and pulmonary nodules system. 1,917 overseas returnees who underwent CT examination and rRT-PCR tests were enrolled. DL pneumonia system promptly alerted clinicians to suspected COVID-19 after CT examinations while the performance was evaluated with rRT-PCR results as the reference. The radiological features of asymptomatic COVID-19 cases were described according to the Nomenclature of the Fleischner Society.&nbsp;</p><p>Results: Fifty-three cases were confirmed as COVID-19 patients by rRT-PCR tests, including 5 asymptomatic cases. DL pneumonia system correctly alerted 50 cases as suspected COVID-19 with a sensitivity of 0.9434 and specificity of 0.9592 (within 2 minutes per case); while the pulmonary nodules system alerted 2 of the 3 missed asymptomatic cases. Additionally, five asymptomatic patients presented different characteristics such as elevated creatine kinase level and prolonged prothrombin time, as well as atypical radiological features.</p><p>Conclusions: DL diagnostic systems are promising complementary approaches for prompt screening of imported COVID-19 patients, even the imported asymptomatic cases. Unique clinical and radiological characteristics of asymptomatic cases might be of great value in screening as well.&nbsp;</p><p>Advances in knowledge: DL-based systems are practical, efficient, and reliable to assist radiologists in screening COVID-19 patients. Differential features of asymptomatic patients might be useful to clinicians in the frontline to differentiate asymptomatic cases.</p> ER -