基于模糊云的COVID-19诊断助手，用于使用多准则决策方法在全球范围内识别受影响病例。
Fuzzy Cloud Based COVID-19 Diagnosis Assistant for identifying affected cases globally using MCDM.
作者信息
Ahmad Shahnawaz, Mehfuz Shabana, Beg Javed, Ahmad Khan Nadeem, Husain Khan Afzal
机构信息
Department of Electrical Engineering, Jamia Millia Islamia (A Central University), New Delhi-110025, India.
Oracle, India.
出版信息
Mater Today Proc. 2021 Jan 29. doi: 10.1016/j.matpr.2021.01.240.
The COVID-19, Coronavirus Disease 2019, emerged as a hazardous disease that led to many causalities across the world. Early detection of COVID-19 in patients and proper treatment along with awareness can help to contain COVID-19. Proposed Fuzzy Cloud-Based (FCB) COVID-19 Diagnosis Assistant aims to identify the patients as confirmed, suspects, or suspicious of COVID-19. It categorized the patients into four categories as mild, moderate, severe, or critical. As patients register themselves online on the FCB COVID-19 DA in real-time, it creates the database for the same. This database helps to improve diagnostic accuracy as it contains the latest updates from real-world cases data. A team of doctors, experts, consultants are integrated with the FCB COVID-19 DA for better consultation and prevention. The ultimate aim of this proposed theory of FCB COVID-19 DA is to take control of COVID-19 pandemic and de-accelerate its rate of transmission among the society.
2019冠状病毒病（COVID-19）是一种危险疾病，在全球导致了许多死亡病例。对患者进行COVID-19的早期检测，并给予适当治疗以及提高认识，有助于控制COVID-19。提出的基于模糊云的（FCB）COVID-19诊断助手旨在将患者识别为确诊、疑似或可疑COVID-19病例。它将患者分为轻度、中度、重度或危重症四类。当患者实时在FCB COVID-19诊断助手上进行在线注册时，它会创建相应的数据库。该数据库有助于提高诊断准确性，因为它包含来自真实病例数据的最新更新。一组医生、专家、顾问与FCB COVID-19诊断助手整合，以进行更好的会诊和预防。所提出的FCB COVID-19诊断助手理论的最终目标是控制COVID-19大流行，并减缓其在社会中的传播速度。
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