A Review on COVID-19 Patients Detection Using Data Mining and IoT Technology

Rabie, Asmaa H.; Mansour, Nehal A.; Al-Husseiny, Amal; Saleh, Ahmed I.

A Review on COVID-19 Patients Detection Using Data Mining and IoT Technology

Document Type : Original Article

Authors

¹ computer and control syestem dep,Faculty of Engineering , Mansoura university,Egypt

² Nile Higher Institute for Engineering and Technology, Artificial intelligence Lab., Mansoura, Egypt

Abstract

Early detection of COVID-19 patients is an important issue for disease cure and control. COVID-19 has not been previously identified in humans because it is a new species appeared in 2019. Unfortunately, COVID-19 spreads so quickly between people in few months. The most common symptoms of COVID-19 that can progress to a severe form of pneumonia with critical complications are dry cough, sore throat, and fever. In fact, clinical characteristics alone cannot determine the diagnosis of COVID-19 patients at the early-onset of symptoms. Thus, it is an important to find fast and accurate COVID-19 patients detection model that can quickly and accurately diagnose the patients. In this paper, many classification methods which can early detect COVID-19 patients are discussed. In fact, data mining is an effective tool that can be used in predicting medical conditions. Data mining can enable caregivers to accurately make medical decisions. Nowadays, Internet of Things (IoT) is implemented in the infrastructure of the medical system that leads to make the system more automated and enable the medical staff to monitor COVID-19 patients remotely.

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