Chinese experts’ consensus on the Internet of Things-aided diagnosis and treatment of coronavirus disease 2019 (COVID-19)

Li Bai(Army Medical University), Dawei Yang(Fudan University), Xun Wang(Xian Yang Central Hospital), Tong Lin(Fudan University), Xiaodan Zhu(Fudan University), Nanshan Zhong(Guangzhou Medical University), Chunxue Bai(Fudan University), Charles A. Powell(Icahn School of Medicine at Mount Sinai), Rongchang Chen(ShenZhen People’s Hospital), Jian Zhou(Fudan University), Yuanlin Song(Fudan University), Xin Zhou(Shanghai First People's Hospital), Huili Zhu(Fudan University), Baohui Han(Shanghai Jiao Tong University), Qiang Li(Shanghai East Hospital), Guochao Shi, Shengqing Li(Fudan University), Changhui Wang(Shanghai Tenth People's Hospital), Zhongmin Qiu(Tongji University), Yong Zhang(Fudan University), Yu Xu(Fudan University), Jie Liu(Fudan University), Ding Zhang(Fudan University), Chaomin Wu(Fudan University), Jing Li(Fudan University), Jinming Yu(Fudan University), Jiwei Wang(Shanghai Tenth People's Hospital), Chunling Dong(Fudan University), Yaoli Wang(Shanghai Tenth People's Hospital), Qi Wang(Shanghai Tenth People's Hospital), Lichuan Zhang(Fudan University), Min Zhang(Fudan University), Xia Ma(Fudan University), Lin Zhao(Fudan University), Wencheng Yu(Fudan University), Tao Xu(Fudan University), Yang Jin(Fudan University), Xiongbiao Wang(Shanghai Tenth People's Hospital), Yuehong Wang(Shanghai Tenth People's Hospital), Yan Jiang(Fudan University), Hong Chen(ShenZhen People’s Hospital), Kui Xiao(Fudan University), Xiaoju Zhang(Fudan University), Zhenju Song(Fudan University), Ziqiang Zhang(Fudan University), Xueling Wu(Fudan University), Jiayuan Sun(Fudan University), Yao Shen(Fudan University), Maosong Ye(Fudan University), Chunlin Tu(Fudan University), Jinjun Jiang(Fudan University), Hai Yu(Fudan University), Fei Tan(Fudan University)
Clinical eHealth
January 1, 2020
Cited by 224Open Access
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Abstract

The aim is to diagnose COVID-19 earlier and to improve its treatment by applying medical technology, the “COVID-19 Intelligent Diagnosis and Treatment Assistant Program (nCapp)” based on the Internet of Things. Terminal eight functions can be implemented in real-time online communication with the “cloud” through the page selection key. According to existing data, questionnaires, and check results, the diagnosis is automatically generated as confirmed, suspected, or suspicious of 2019 novel coronavirus (2019-nCoV) infection. It classifies patients into mild, moderate, severe or critical pneumonia. nCapp can also establish an online COVID-19 real-time update database, and it updates the model of diagnosis in real time based on the latest real-world case data to improve diagnostic accuracy. Additionally, nCapp can guide treatment. Front-line physicians, experts, and managers are linked to perform consultation and prevention. nCapp also contributes to the long-term follow-up of patients with COVID-19. The ultimate goal is to enable different levels of COVID-19 diagnosis and treatment among different doctors from different hospitals to upgrade to the national and international through the intelligent assistance of the nCapp system. In this way, we can block disease transmission, avoid physician infection, and epidemic prevention and control as soon as possible.


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