COVID19 patient’s detection and localization by using an expert intelligent system

Coronaviruses are a vast category of viruses that cause illnesses ranging from colds to more serious illnesses like Middle East Respiratory Syndrome (MERS-CoV) and Severe Acute Respiratory Syndrome (SARS-CoV) (SARS-CoV). The emerging coronavirus (nCoV) is a novel coronavirus strain that has never be...

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Bibliographic Details
Main Authors: Anooz, Ruaa Shallal Abbas, Abdulsadda, Ahmad Taha, Al-Dulaimi, Aymen M. Khodayer
Format: Conference Proceeding
Language:English
Subjects:
Algorithms
Applications programs
Coronaviruses
Expert systems
Illnesses
Mobile computing
Multilayer perceptrons
Neural networks
Respiratory diseases
Severe acute respiratory syndrome
Viral diseases
Viruses
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Summary:Coronaviruses are a vast category of viruses that cause illnesses ranging from colds to more serious illnesses like Middle East Respiratory Syndrome (MERS-CoV) and Severe Acute Respiratory Syndrome (SARS-CoV) (SARS-CoV). The emerging coronavirus (nCoV) is a novel coronavirus strain that has never been seen in humans before. In the current work, we proposed an effective approach with developing the expert system focused on using the 4 G or 5 G cell networks to find the patients where they are and send the warning signal to the clinic station. When the important thing about containing the COVID19 virus is detecting, the human how it reached it and distinguishing it from the others, this step would be very helpful to constraints and would safeguard others. The patient how viruses had recently had three main symptoms of pain in the throat, redness in the eyes, and finally fever. Our proposed algorithm is to use the mobile application system Multilayer perceptron neural networks to determine, whether the person with the device is infected or not, the simulation findings demonstrate that a patient with the signs of the virus successfully identified in the system.
ISSN:0094-243X
1551-7616
DOI:10.1063/5.0163171