Accepted for/Published in: JMIR mHealth and uHealth
Date Submitted: Nov 18, 2022
Open Peer Review Period: Dec 7, 2022 - Feb 7, 2023
Date Accepted: Aug 18, 2023
Date Submitted to PubMed: Jan 17, 2024
(closed for review but you can still tweet)
Mobile applications in COVID-19 detection and diagnosis: an efficient tool to control the future pandemic; a multidimensional systematic review of the state of the art
ABSTRACT
Background:
In the modern world, mobile applications are essential to human advancement and pandemic control is no exception. The use of mobile applications and technology for the detection and diagnosis of COVID-19 disease has been the subject of numerous investigations.
Objective:
Since no thorough analysis of the COVID-19 epidemic prevention has been done using mobile applications. Due to this gap, the current study thoroughly covers the many uses of mobile applications for COVID-19 detection and diagnosis.
Objective:
Since no thorough analysis of the COVID-19 epidemic prevention has been done using mobile applications. Due to this gap, the current study thoroughly covers the many uses of mobile applications for COVID-19 detection and diagnosis.
Methods:
A search of five major research databases (ScienceDirect, Scopus, PubMed, Web of Science, IEEE) found 535 studies, among which 42 related to the diagnosis and detection of patients suspected of having COVID-19.
Results:
Mobile applications can be categorized into five areas based on the content of these studies: contact tracing, data gathering, data visualization, artificial intelligence-based methods, rule- and guideline-based methods, and data transformation. Patients with COVID-19 have been identified using mobile applications employing a variety of clinical, geographic, demographic, radiological, serological, and laboratory data. The majority of studies concentrated on using artificial intelligence (AI) methods to identify people who might have COVID-19. Additionally, compared to other data types, symptoms, cough sounds, and radiological images were used more frequently.
Conclusions:
Mobile applications could soon play a significant role as a powerful tool for data collection, epidemic health data analysis, and early identification of suspected cases. These technologies can work in conjunction with the Internet of Things (IoT), cloud storage, 5G, and cloud computing.
Citation
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.